{"as_of":"2026-08-17T19:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1077f9369a74134c255a8729a92c7f0b80dbaf9749f40f2912fc96ffe500b2f8","coverage":[{"denominator":74,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":74,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:48:26.064062Z","state":"measured"},{"denominator":75,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":75,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:14:18.321828Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T15:14:19.138571Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"cited_work":{"arxiv_id":"2412.02225","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.02225","snapshot_observed_at":"2026-08-06T15:14:19.138571Z","title":"How to Use Diffusion Priors under Sparse Views?","venue":"cs.CV","work_id":"966f77e0-7dc6-4f35-a950-11a9b8d714f2","year":2024},"citing_paper":{"arxiv_id":"2507.16406","last_updated":"2025-07-22T09:57:28Z","snapshot_observed_at":"2026-08-13T03:24:20.990465Z","submitted_at":"2025-07-22T09:57:28Z","title":"Sparse-View 3D Reconstruction: Recent Advances and Open Challenges","version":1},"reference_index":138,"source":"pdf_text","source_observed_at":"2026-08-06T15:14:18.321828Z"},"links":{"cited_paper":"/paper/2412.02225","citing_paper":"/paper/2507.16406"},"observation_digest":"sha256:0b2b63163668cbeb75bfec15b5f8f485d9c9705cf32bb93b85ae0412929e6098","observation_id":"8ec67b66-afe1-4b47-9346-e51d09881a5d","resolution":{"observed_at":"2026-08-06T15:14:19.142456Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.02225/citation-record","integrity":"/paper/2412.02225/integrity","json":"/paper/2412.02225/citation-record.json","paper":"/paper/2412.02225"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:24.186825Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.186825Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:2dab41900082c7d6d64fb6fbbdf8cf90fd40065d150f43858c4bb8b1b23b49d6","observation_id":"a307ceb6-bbca-4fb8-8948-23bf3dbcd961","resolution":{"observed_at":"2026-08-11T23:48:24.186825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.477718Z","title":"3d gaussian splatting for real-time radiance field rendering,","venue":null,"work_id":"75719ccc-de3e-4d06-91ec-d69a05c8bf8a","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.238458Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:c3f010c528aa0076a252beb00f3e3fbad094139232330e58bd9afd1d1baba72e","observation_id":"0492eec8-274d-4c5b-b9a5-ac7658463b9c","resolution":{"observed_at":"2026-08-11T23:48:28.483194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03000","last_updated":"2024-03-18T18:09:58Z","snapshot_observed_at":"2026-08-16T15:26:28.894289Z","submitted_at":"2023-06-05T16:10:21Z","title":"BeyondPixels: A Comprehensive Review of the Evolution of Neural Radiance Fields","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03000","snapshot_observed_at":"2026-08-11T23:48:24.337781Z","title":"Beyondpixels: A comprehensive review of the evolution of neural radiance fields,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.337781Z"},"links":{"cited_paper":"/paper/2306.03000","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:61c15985788790112c04357060e234251b93f71e62a668c223ff55ed47ffbfd6","observation_id":"2db27cb4-475e-4625-8bb9-d9f4019245a1","resolution":{"observed_at":"2026-08-11T23:48:24.337781Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.00379","last_updated":"2026-02-12T16:09:50Z","snapshot_observed_at":"2026-07-06T13:58:37.592838Z","submitted_at":"2022-10-01T21:35:11Z","title":"NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.00379","snapshot_observed_at":"2026-08-11T23:48:24.431614Z","title":"Nerf: Neural radiance field in 3d vision, a comprehensive review,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.431614Z"},"links":{"cited_paper":"/paper/2210.00379","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:6fb169618114b370cf34a3ed0090fa60e03dad9cdd2afb155bfa7f66d45c63e0","observation_id":"d09ea3e1-c101-4ebb-adce-ce682c24a6cb","resolution":{"observed_at":"2026-08-11T23:48:24.431614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03890","last_updated":"2026-04-09T05:33:48Z","snapshot_observed_at":"2026-08-09T09:22:22.467803Z","submitted_at":"2024-01-08T13:42:59Z","title":"A Survey on 3D Gaussian Splatting","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03890","snapshot_observed_at":"2026-08-11T23:48:24.455066Z","title":"A survey on 3d gaussian splatting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.455066Z"},"links":{"cited_paper":"/paper/2401.03890","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:b7f0405af3cd2869cf115aefdd51ee706f52c9202d7d1d3085c94a276c1c0af8","observation_id":"238d0308-4c61-4404-958c-ed4077f6ae09","resolution":{"observed_at":"2026-08-11T23:48:24.455066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07181","last_updated":"2024-07-10T02:48:08Z","snapshot_observed_at":"2026-08-16T14:19:34.111983Z","submitted_at":"2024-02-11T12:33:08Z","title":"3D Gaussian as a New Era: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07181","snapshot_observed_at":"2026-08-11T23:48:24.481674Z","title":"3d gaussian as a new vision era: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.481674Z"},"links":{"cited_paper":"/paper/2402.07181","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:8ed71e93c4e1b40dc92b6e7563f2ed4ea853fc66e623f96672ff83915bcd3179","observation_id":"ed9a7386-1045-4435-89a6-96633c6ce535","resolution":{"observed_at":"2026-08-11T23:48:24.481674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.461560Z","title":"Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs,","venue":null,"work_id":"491184bc-011d-471b-be46-b3dd681085cd","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.488025Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:16507808298c68edfc92342985c74090bf65237e2328e3505fc1bcb2cb4f23f0","observation_id":"8f73d4b5-a6b8-4954-9d1a-0721b32e43ac","resolution":{"observed_at":"2026-08-11T23:48:28.466488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.444115Z","title":"Freenerf: Improving few-shot neural rendering with free frequency regularization,","venue":null,"work_id":"cfba1326-b9d4-4876-8cc6-9e072fb70dac","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.492950Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:8322da6fe19686e3660c95aaa5c2cef6cb5ff06dbfff6d8396aa6309f9a3f322","observation_id":"1b85537b-0849-465e-9b7e-dcd6abc9ce94","resolution":{"observed_at":"2026-08-11T23:48:28.449767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.333286Z","title":"Dngaussian: Optimizing sparse-view 3d gaussian radiance fields with global-local depth normalization,","venue":null,"work_id":"ccab0255-f279-475d-8e3c-d0bde2da250d","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.498487Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:300da67783524aa01d7d52778a92a509bc6aed7b3949e525bb8418842ac17309","observation_id":"626c0a1a-09fb-4260-9d7c-086fe59f52e5","resolution":{"observed_at":"2026-08-11T23:48:28.415609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.263293Z","title":"Putting nerf on a diet: Semantically consistent few-shot view synthesis,","venue":null,"work_id":"0fa90dbe-5f2d-495d-af46-f937830b5275","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.503941Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0752ce7c3a81f74fc9c3b6a289fcb2c9b9f6c098b55083647c10ce2ad8e3b73f","observation_id":"2c224024-c635-4061-945b-a65ceb5ce645","resolution":{"observed_at":"2026-08-11T23:48:28.276864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.246217Z","title":"Depth-supervised nerf: Fewer views and faster training for free,","venue":null,"work_id":"fd6c4a80-e3ac-49b1-8100-785f913c0817","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.508913Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:dff513a0bcd8b42d3308ba235a6eb1e83492d8558cdb6632da9c6ffba74a1172","observation_id":"090d89ce-5f1d-4b74-bcd9-7d5398978fab","resolution":{"observed_at":"2026-08-11T23:48:28.252244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.229997Z","title":"Sparsenerf: Distilling depth ranking for few-shot novel view synthesis,","venue":null,"work_id":"25463ae6-3390-40d8-a297-e5d6aaaafff9","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.513859Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:cda14ebdb42996264bfbcfd778ab3ad2e6a0b3cd22673a65c57ebae0861a5791","observation_id":"82c83582-f825-44ce-85c0-c59975d43a83","resolution":{"observed_at":"2026-08-11T23:48:28.235446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.213849Z","title":"Learning transferable visual models from natural language supervi- sion,","venue":null,"work_id":"7a2f1b5b-9ae4-4933-b7a9-12ef3c91b8f0","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.518209Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:1f00f173216fc419c2c4c7d39adc36dcd16c81e74e0611186b5df16658c84e6e","observation_id":"04001af0-694a-4ac3-885d-b80091908637","resolution":{"observed_at":"2026-08-11T23:48:28.219558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00206","last_updated":"2026-06-23T19:23:37Z","snapshot_observed_at":"2026-08-16T14:38:39.788471Z","submitted_at":"2023-11-30T21:38:22Z","title":"SparseGS: Sparse View Synthesis using 3D Gaussian Splatting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00206","snapshot_observed_at":"2026-08-11T23:48:24.538560Z","title":"Sparsegs: Real-time 360 {\\deg} sparse view synthesis using gaussian splatting,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.538560Z"},"links":{"cited_paper":"/paper/2312.00206","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:a082771cdc0dda958cfd684b043cb29777b84262887576e7737f3182626fd6b9","observation_id":"77ae3e98-b8d4-49b9-b93d-1c0dbef3968e","resolution":{"observed_at":"2026-08-11T23:48:24.538560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.197828Z","title":"Reconfusion: 3d reconstruction with diffusion priors,","venue":null,"work_id":"af192f9c-730d-43f7-8177-144c3be43528","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.659230Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:c1865b3ee4616f32cddc59bbf5604dbac13c4cd8d4a568c533a1b00b4f82a20e","observation_id":"93f3bc6a-4c70-4018-905b-06c51a8044cb","resolution":{"observed_at":"2026-08-11T23:48:28.203041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.181869Z","title":"Deceptive-nerf/3dgs: Diffusion- generated pseudo-observations for high-quality sparse-view reconstruction,","venue":null,"work_id":"1a7d84e0-f594-411c-ae0b-2c65f103f7c2","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.747607Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:f42107a24e45ab264b68db23cb1cd8563c080908dfddf78322e8dd8db72ce290","observation_id":"50f9080a-024c-49ca-b1c8-697e7b4ab83a","resolution":{"observed_at":"2026-08-11T23:48:28.187089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.164960Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics,","venue":null,"work_id":"2b8188f5-9c3d-4f7c-bde2-cffa7c5b62d9","year":2015},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.810689Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:ad9a226881f58dcfc0b1c572615ff8cc0e2120ae484ee5bde59671ff5f082547","observation_id":"c6935690-871a-44cf-9a94-96c80fc4fe7f","resolution":{"observed_at":"2026-08-11T23:48:28.170541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.147145Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":"29ca1c35-d667-4a59-aec8-887baebb8b7d","year":2020},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.829269Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:a31f5cee170591916dbc8783bfd5c11cf3ae542ba7dfbb7b97d9cb88677b35f9","observation_id":"2a526553-9f53-47dc-9b10-9a42ed9918de","resolution":{"observed_at":"2026-08-11T23:48:28.152909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.092870Z","title":"Score-based generative modeling through stochastic differential equations,","venue":null,"work_id":"fd3ddfb8-291d-419d-b026-8191da7a3bd1","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.859070Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0f6b65133feaa95874e99aa1ca070f7780b87f180cc36e160c006115b059e187","observation_id":"4b465b66-3be8-4660-ba62-9ab0d6b6cd24","resolution":{"observed_at":"2026-08-11T23:48:28.127808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:28.025067Z","title":"Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models,","venue":null,"work_id":"fd38fbef-2bd9-4f99-8e95-1a60488f585f","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.867922Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:756f73cadfc9452dd751c665ddf9a62006a636981b2a97dfe6ba6d0396631a11","observation_id":"70c23fe8-103d-407f-b7ec-e813ab540595","resolution":{"observed_at":"2026-08-11T23:48:28.052212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.928145Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":"ada4c391-e5ef-42be-aa7f-5311de559299","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.872998Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:3607a21d48cdb1f941f9b67bb5bd230e25632170c3c4576e9b353f742b1fff16","observation_id":"5566c14c-fb60-4aa9-941e-276002d6aff2","resolution":{"observed_at":"2026-08-11T23:48:27.966280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.898267Z","title":"Local light field fusion: Practical view synthesis with prescriptive sampling guidelines,","venue":null,"work_id":"379343af-f9e6-4c77-a2ff-4a1699ae3b8d","year":2019},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.879008Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:a819cdce12bda5465e49d5389a208216e6f31269f0aa3d4cc6fb0e6bfadfcb54","observation_id":"bab2ee41-1906-4881-97c6-a2f8763bdabc","resolution":{"observed_at":"2026-08-11T23:48:27.903862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.882435Z","title":"Dreamfusion: Text-to-3d using 2d diffusion,","venue":null,"work_id":"4b597950-828c-4be7-9eef-a89dcaf6fb61","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.884130Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:e3d56b88947309ba0137f5757367ff649a218c22801e38c498439cba4047924f","observation_id":"d12203f9-778c-4222-a441-bd0041c2fcab","resolution":{"observed_at":"2026-08-11T23:48:27.887783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.867814Z","title":"Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors,","venue":null,"work_id":"bfabf80e-7dd6-4d9b-8464-617ac3a87059","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.889388Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:d3b087ee24207318c6916096e9b5f08a6aa851e241de93ea33e4e5c568c0881d","observation_id":"87d8b6c6-ae23-40a0-8708-e5987e4e70d4","resolution":{"observed_at":"2026-08-11T23:48:27.872750Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.850976Z","title":"Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation,","venue":null,"work_id":"1ea0cd24-43a5-400f-b963-d268f960df14","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.895641Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:52585565397dbc633d4cd76d5d278cd218def70cbd0dcb250ced4278292cdca1","observation_id":"c66660db-f5b6-4078-98eb-d5a869ee4bcb","resolution":{"observed_at":"2026-08-11T23:48:27.856161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.833869Z","title":"Luciddreamer: Towards high-fidelity text-to-3d generation via interval score matching,","venue":null,"work_id":"9e74775f-a41b-44a9-84bc-f3dc3a46d2e7","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.900902Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:bfda29d768955d1ecd9ca8d389a66096aa00de4bea6dfd520f3f80950437146e","observation_id":"8df125d5-74a9-4618-8191-415675b6a987","resolution":{"observed_at":"2026-08-11T23:48:27.839761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.816981Z","title":"Novel view synthesis in tensor space,","venue":null,"work_id":"af590f48-c2fe-4504-ab45-a594aacf2030","year":1997},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.932165Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0d14564e52bfefa690bd69e53319ffe234430ceccb5fb28ce54826f1b6c74dc8","observation_id":"e275f195-5569-4552-be70-fc64cf5a6858","resolution":{"observed_at":"2026-08-11T23:48:27.822510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.800376Z","title":"Instant neural graphics primitives with a multiresolution hash encoding,","venue":null,"work_id":"b2a60871-7a1f-44d1-a102-27a03c1cfe1e","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:24.990355Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:e3bb5caea9cd99e1c370a6cbe4d7c5bd047bd2e4447f941b4da22519de4b21c9","observation_id":"0a4887b1-86ea-428e-93cd-a9295066cb57","resolution":{"observed_at":"2026-08-11T23:48:27.805973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.714201Z","title":"Plenoxels: Radiance fields without neural networks,","venue":null,"work_id":"5e1726b7-4724-406e-bc78-1558bd4a43e2","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.118371Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:06e11811ee46fbd355e2dbdf09d9983a7626e5b448dabfccae772aca09a59650","observation_id":"319d9185-434a-4e71-9815-a30aacaf34b7","resolution":{"observed_at":"2026-08-11T23:48:27.749544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.637869Z","title":"Tensorf: Tensorial radiance fields,","venue":null,"work_id":"d29bd5b9-a9a7-416e-af04-a7208fb65b06","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.180741Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:7ca1e211dcbd1432501915736874ce9ae4bf843832a9ffa187abb6228d311452","observation_id":"f2a57b5b-02bb-41f7-8551-5d3fe25746bc","resolution":{"observed_at":"2026-08-11T23:48:27.664859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.595248Z","title":"D-nerf: Neural radiance fields for dynamic scenes,","venue":null,"work_id":"aab6ab3e-9a8b-42f2-b8fc-5598de6a9773","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.244844Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:c2a5c0ed8bc91afe08a75cdff16d488fac100de2b781da41271cf638c43fd0df","observation_id":"6099370a-4913-4e74-bd01-dcd9aab69d3c","resolution":{"observed_at":"2026-08-11T23:48:27.600964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.579077Z","title":"Nerf in the wild: Neural radiance fields for unconstrained photo collections,","venue":null,"work_id":"3d4074fc-a27f-4b3a-931b-3d58cb1daa64","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.261981Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:2e2baaf92880379fdc85c69f7225ebd33450e5a3d0a0bcef2f4b075dfdb7acb0","observation_id":"dfe3f69b-1789-4a70-b846-6d94d65b326f","resolution":{"observed_at":"2026-08-11T23:48:27.584240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.562675Z","title":"Block-nerf: Scalable large scene neural view synthesis,","venue":null,"work_id":"0dc5909c-68ea-46fd-b1bf-3c33f2bbf5ea","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.268143Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:d8985383db436c7c571c640362cd5e2cdaac2f93c85d206e6c9e1d860dcc2cb4","observation_id":"1a4d9925-46b7-4999-b6a5-cf4067e6786c","resolution":{"observed_at":"2026-08-11T23:48:27.567202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.546340Z","title":"Ref-nerf: Structured view-dependent appearance for neural radiance fields,","venue":null,"work_id":"22540fba-3ede-4eea-9382-3182e983d66b","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.274153Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:08f3cc01df32c7ea35edb29a1652200c116292b8610367245c1a7e1492b358a9","observation_id":"ff360688-66d1-4c02-a16d-6a5659b91f76","resolution":{"observed_at":"2026-08-11T23:48:27.551891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.529081Z","title":"Mip-nerf 360: Unbounded anti-aliased neural radiance fields,","venue":null,"work_id":"8f9217d1-b68b-4e5a-84da-7d5b1edd1787","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.278974Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0acf0c97bb747d48e993dbeb066ca6c5d5e3525fa51fcda526bfe046b585aa98","observation_id":"0b3955c6-562b-444e-acbc-b5b8c5c0f03e","resolution":{"observed_at":"2026-08-11T23:48:27.534339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.513608Z","title":"Barf: Bundle-adjusting neural radiance fields,","venue":null,"work_id":"72c6c92e-714c-4bf0-be49-2c1833b01f77","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.283682Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:bd69fe90d9b85030882fa0d2e9c39f5d6f665931e7c297c5aa4ffc6b0ae843a3","observation_id":"199ff64f-5f7a-4db6-a3f2-f7c22a907806","resolution":{"observed_at":"2026-08-11T23:48:27.518144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.497943Z","title":"Neural sparse voxel fields,","venue":null,"work_id":"a0d087b9-6e18-41ac-8956-d5e36941797e","year":2020},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.288947Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:cc772c709ed1aa1a0ee3b4d5d4a591a45f5cb4b99be8783d485f6537fd5c1b03","observation_id":"6b9c4721-8e52-4009-8cbf-e51fe9afa789","resolution":{"observed_at":"2026-08-11T23:48:27.502611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.480842Z","title":"Drivinggaussian: Composite gaussian splatting for surrounding dynamic autonomous driving scenes,","venue":null,"work_id":"f13c732a-0b47-4eef-b9ee-8ab3faad4ead","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.294325Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:421fa01d0dd791ea04d4e111e3736fac60d39d56aca64c462d24afad845bec6a","observation_id":"81e0dfd6-345e-478f-bab1-04b8baef464d","resolution":{"observed_at":"2026-08-11T23:48:27.486992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.464136Z","title":"Splattingavatar: Realistic real-time human avatars with mesh-embedded gaussian splatting,","venue":null,"work_id":"6943dcf1-67a1-45de-b219-331451d9b27d","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.298954Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:00c5bef79fa65e9a325fe1d5ab2bbe140c84684eaa4e7457a2e6d8db50deff50","observation_id":"f2fa562d-f024-4b40-aef4-f7efe9801e38","resolution":{"observed_at":"2026-08-11T23:48:27.469435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.445806Z","title":"Animatable gaussians: Learning pose-dependent gaussian maps for high-fidelity human avatar modeling,","venue":null,"work_id":"bbc1d68a-bad7-436e-ba27-318861ec1d13","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.303194Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:07e7ec5cc3b8d12c85152d713ccf0e4cb87b3f75d479b5899d3ef8ea784e39fe","observation_id":"a912b85a-950c-44f6-a689-4219e99ea559","resolution":{"observed_at":"2026-08-11T23:48:27.451257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.316117Z","title":"Hifi4g: High-fidelity human performance rendering via compact gaussian splatting,","venue":null,"work_id":"4ad9241e-3728-41ba-af95-e8a0d953b1d9","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.308435Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:12fca3c9c0262352a32285271d2c9f0e71a8d49805ee1895846befa05c3e014b","observation_id":"f32cd202-d023-4521-b93d-f291893449b9","resolution":{"observed_at":"2026-08-11T23:48:27.377513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.215128Z","title":"Dreamgaussian: Generative gaussian splatting for efficient 3d content creation,","venue":null,"work_id":"afb4b4ed-10be-4ce6-86fe-927f60e329b4","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.313455Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0280f4b3ad33960072bf61a8443890dc5feacb972e04f8ad8018eed82afdd3c7","observation_id":"af6dfe6d-3131-4951-a1d0-2f88d814f8d4","resolution":{"observed_at":"2026-08-11T23:48:27.239761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.200060Z","title":"Flipnerf: Flipped reflection rays for few-shot novel view synthesis,","venue":null,"work_id":"460e62ad-b98f-4e06-914a-2b2cd313d070","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.318236Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:97db6c26a736dbebe9ef835066bb46324658dd570ab25b06362030a0b6d0a4fd","observation_id":"f3754496-da6b-450f-b6cf-7f09c70d2488","resolution":{"observed_at":"2026-08-11T23:48:27.205257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.184199Z","title":"Därf: Boosting radiance fields from sparse input views with monocular depth adaptation,","venue":null,"work_id":"ad658c3f-7419-4abb-b6cb-745baa71596a","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.342160Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:a2a72dd3ad4ec799c58078b58573d90643c162732635c8939d8631c5b689ebd3","observation_id":"cee454be-c236-4e97-ac52-2248f62a122a","resolution":{"observed_at":"2026-08-11T23:48:27.189607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.169461Z","title":"Simplenerf: Regularizing sparse input neural radiance fields with simpler solutions,","venue":null,"work_id":"6045e60d-64e2-4078-8d9e-252ca68efbb8","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.429851Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:20891ce963fe02f72bb36c2aafb84c598e08dda5f54cfab368e29562e9cd819b","observation_id":"1449777f-4395-420e-a8cb-1e7dd244f791","resolution":{"observed_at":"2026-08-11T23:48:27.174256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.154289Z","title":"Geconerf: Few-shot neural radiance fields via geometric consistency,","venue":null,"work_id":"e4831eb7-b549-4730-a234-4098ec56ecb5","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.508722Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:2c86e5ad2d264bcd8d633d976a1026fe373e94c9020e653adb0120ec9eeec1ee","observation_id":"7410e576-c424-4d65-bd9a-2852de89f7a3","resolution":{"observed_at":"2026-08-11T23:48:27.159149Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.136633Z","title":"Geoaug: Data augmentation for few-shot nerf with geometry constraints,","venue":null,"work_id":"f6b4ed4f-f83d-4079-87f1-85819844c35a","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.573927Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:96ada98a6974045e6c238c1ac8fcb721964f7e6d6350ce3bf3f4a2dd8ae71c13","observation_id":"3fc2e9c6-74b0-4577-9c54-eff5c4fedaa9","resolution":{"observed_at":"2026-08-11T23:48:27.142004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.112561Z","title":"Vision transformers for dense prediction,","venue":null,"work_id":"f157e09e-54e9-4a00-8e26-0b988c429ae3","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.603257Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:8de828767436fe09b5d39376b6f20ed586afb6be897b532452ae0d13639fc2e1","observation_id":"ddf2c465-fc02-43e9-89a0-03adcd8a00bd","resolution":{"observed_at":"2026-08-11T23:48:27.124072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:27.095874Z","title":"pixelnerf: Neural radiance fields from one or few images,","venue":null,"work_id":"e8e910a5-f8dc-4b77-ad0f-cf956497bce4","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.643333Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:937227e0fc9e5accb669e2611626745a21a87845a796d2c499fc047c06b6f0f4","observation_id":"91d67a35-3058-4460-96d2-b75a7e173984","resolution":{"observed_at":"2026-08-11T23:48:27.101046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.966022Z","title":"Zero-1-to-3: Zero-shot one image to 3d object,","venue":null,"work_id":"39a0ce9f-8c3c-484f-bf0a-c7fdf8a43f0f","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.652779Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:6c11a60a8e243245962745155dfa57ee629c0d4bcefbf92f5743cf982839b046","observation_id":"60c376f3-d580-4ee0-9ea7-ae3f63875d87","resolution":{"observed_at":"2026-08-11T23:48:27.026718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.949349Z","title":"Zeronvs: Zero-shot 360-degree view synthesis from a single image,","venue":null,"work_id":"96c67f83-5747-4d43-be81-60f73c247a9f","year":2024},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.657447Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:390de6ba45470196ffbbf8a60bc32900294ec38a0ac798145232961e4ab1ee22","observation_id":"92e8e4af-97e2-4a38-9b67-7f64f73a9c8d","resolution":{"observed_at":"2026-08-11T23:48:26.954725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.929119Z","title":"invs: Repurposing diffusion inpainters for novel view synthesis,","venue":null,"work_id":"c6cd9f62-a6c4-46f8-973f-2df7ab5f14f0","year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.663617Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:82d7427f0b644c658937d7233dbfd3bc9dcd301bfb102f51038473de4bc8a22b","observation_id":"5256fdb5-4d11-4df1-9492-c0665f1da816","resolution":{"observed_at":"2026-08-11T23:48:26.936611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.09305","last_updated":"2024-02-07T08:15:51Z","snapshot_observed_at":"2026-08-16T14:34:37.647139Z","submitted_at":"2023-12-14T19:18:38Z","title":"Stable Score Distillation for High-Quality 3D Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09305","snapshot_observed_at":"2026-08-11T23:48:25.668728Z","title":"Stable score distillation for high-quality 3d generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.668728Z"},"links":{"cited_paper":"/paper/2312.09305","citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:0273dd23710d3bd172c5f7aa5a7b48a23fbd04b25f0c7e314154488890a627ec","observation_id":"18721e8c-960d-4996-b2a4-ffd929e829da","resolution":{"observed_at":"2026-08-11T23:48:25.668728Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.911088Z","title":"Large scale multi-view stereopsis evaluation,","venue":null,"work_id":"2987217c-be0c-408f-bbef-fb922d8e6827","year":2014},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.674338Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:92d02214cf1426a8759d08e5d6f840e46bd5bf0df092ccabd19b699d6ee66ae8","observation_id":"fac3d2d0-1f5b-4d5f-b221-d365d66d0e64","resolution":{"observed_at":"2026-08-11T23:48:26.916811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.892519Z","title":"Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes,","venue":null,"work_id":"102cd9bb-6e4d-424c-b973-0e7f6a89f154","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.679162Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:f225e861d6b62ea83355984c61bd29c188d8a25ef05381c800680b78625a304e","observation_id":"890d4fa2-734d-4717-abf1-74c63cb3fc2a","resolution":{"observed_at":"2026-08-11T23:48:26.899638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.875309Z","title":"Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo,","venue":null,"work_id":"47e96786-b5a8-4801-a96f-ee9605f81cdf","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.684002Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:ab0aa63bcae334f5fa25d354d4529aa90180e13e788ec765fe4ecebd5af783f9","observation_id":"d57a34b6-85c1-4b8c-be08-b4b25381aacb","resolution":{"observed_at":"2026-08-11T23:48:26.879857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.817850Z","title":"Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields,","venue":null,"work_id":"2b071b36-6964-4051-a3d2-b99d7bd28717","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.688390Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:76d9bb28cdba21bf0a3db53ebc887da9b2a9193ea6ddc0efb00214f51f16bc8c","observation_id":"36516141-85a7-4084-b97f-36f234cef31e","resolution":{"observed_at":"2026-08-11T23:48:26.854307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.741493Z","title":"Fsgs: Real-time few-shot view synthesis using gaussian splatting,","venue":null,"work_id":"279a2e69-e765-4b98-98d3-33571bb9c09d","year":2025},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.692486Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:93efe3498cc37ff27fa7f4c4bd25f49315b61d43fed7edeb9f79c8ff1227f2b8","observation_id":"77b5fbad-1dac-4526-b45b-39ea75831bca","resolution":{"observed_at":"2026-08-11T23:48:26.785747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:25.696998Z","title":"Image quality assessment: from error visibility to structural similarity,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.696998Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:01a49bbe8ef9437649fd7e7dfdde84ec4f1a3254282e19d5ae8e56db38da46fc","observation_id":"39253779-c8ad-4c12-95b9-38dfc9ab9e7e","resolution":{"observed_at":"2026-08-11T23:48:25.696998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.647188Z","title":"The unreasonable effectiveness of deep features as a perceptual metric,","venue":null,"work_id":"a4717d34-96b4-4209-a5d9-ba1461e21ce4","year":2018},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.702856Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:6aa88c42bb4330af5d804fe388cccd095ba643b64ee4250d56ccbc19a43654b8","observation_id":"34ddcd74-d10e-4970-8df2-e3e3e0ec5286","resolution":{"observed_at":"2026-08-11T23:48:26.668705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.630604Z","title":"Structure-from-motion revisited,","venue":null,"work_id":"2a076c00-d855-4397-b266-f4a77c18eb2a","year":2016},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.726733Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:308a6876ad6b038de009b1f95df4a4e70defa6a669e9a3dc8ba268c390eb2ae5","observation_id":"6343c5ea-120f-45ee-9be3-10a34563eff9","resolution":{"observed_at":"2026-08-11T23:48:26.635485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.614809Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,","venue":null,"work_id":"95ca056e-7ea3-4941-b789-3b8486e98412","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.762550Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:c38ffdf6a5df0b20bea0c6d4c7aceedafef0c18e16fbadf819eaea67447e1d21","observation_id":"1a29919d-9377-4b9f-a651-394179287cc7","resolution":{"observed_at":"2026-08-11T23:48:26.620134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.598978Z","title":"High-resolution image synthe- sis with latent diffusion models,","venue":null,"work_id":"cea78570-7c9f-4a41-89af-88dcc3a4b668","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.876983Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:6c32b678104dc194bee69f6d170884cc16b8d18bae4e82d7de885aed7068fd2e","observation_id":"5f7f30a3-c1ad-4902-8707-ed355f373b58","resolution":{"observed_at":"2026-08-11T23:48:26.604598Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.582834Z","title":"Cor-gs: sparse-view 3d gaussian splatting via co-regularization,","venue":null,"work_id":"94728c8b-90c8-4947-bc1c-2c3a2236f82e","year":2025},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.945149Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:df555aeef4f32e649f22b3d95e37ea71384f7c844484770718d2eef2b34cc87c","observation_id":"1425ce41-b798-42e1-a828-c49d444aa67b","resolution":{"observed_at":"2026-08-11T23:48:26.588673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.566937Z","title":"Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction,","venue":null,"work_id":"9392aed0-7ac4-4d8a-9c47-cc4dd371f048","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.963941Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:69d5d251914fad505d956fb9fcf4142e3e5a0d015108528b437902763f6d41f1","observation_id":"e5dd254d-b65c-4eff-91cc-9277dc895d85","resolution":{"observed_at":"2026-08-11T23:48:26.572226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.551453Z","title":"Development of an image data set of construction machines for deep learning object detection,","venue":null,"work_id":"4240b086-12a0-4b33-9085-0e68e1da68de","year":2021},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:25.984863Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:921563e2639c85cf807e8d3e0957eaa602b228a0f20a7f0155ccb1d0fd3b6ef2","observation_id":"aebff5bb-06a7-48cb-886d-b4c4ba4af766","resolution":{"observed_at":"2026-08-11T23:48:26.556077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.536632Z","title":"Deep learning image captioning in construction manage- ment: a feasibility study,","venue":null,"work_id":"399eb605-6d43-497b-8092-f8b36584e10b","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.009476Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:c7a21eae51b4a15300f11952457c8f888d42de258f8666c2267d6ec3e426995b","observation_id":"eb65ae80-a623-49b3-8df0-93acdb149407","resolution":{"observed_at":"2026-08-11T23:48:26.541757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.521459Z","title":"Stereo magnification: learning view synthesis using multiplane images,","venue":null,"work_id":"ce75e4c0-a63d-44e0-9d63-e06cc3507fdb","year":2018},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.018986Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:b72846bb2177a1092cb38f885ea7dc5ab4d9bfba577fd5d8142c7cce6ca1c326","observation_id":"9bc9e9fe-e770-4fde-b9ca-5edf8b27244a","resolution":{"observed_at":"2026-08-11T23:48:26.526455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.497801Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models,","venue":null,"work_id":"b5d9e98b-f7a5-4b27-be2d-ee894742f428","year":2022},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.027154Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:5fc2cd4e7ef84172238d2bd42f081180bd46d3d4154d63828735dc6214edc316","observation_id":"23188708-0866-43ef-b08e-09c7ad5bafd2","resolution":{"observed_at":"2026-08-11T23:48:26.510305Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.414466Z","title":"Following RegNeRF [7], FreeNeRF [8], and DNGaussian [9], we only use the selected 15 testing scenes for optimization","venue":null,"work_id":"1277e568-622a-4f56-bb58-067e49a1d184","year":null},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.037789Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:de426a792ecff85cb4e9280e1b7c7f35aee7c743c9e3c775fb30882b78313055","observation_id":"de144385-2cf7-401f-bb33-148bf7737c12","resolution":{"observed_at":"2026-08-11T23:48:26.449096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.325914Z","title":"Meanwhile, the reported results of 3DGS [2] are also obtained with the SfM [61] initialization which is the same as ours","venue":null,"work_id":"a94def34-cbf8-4f73-ba66-f5eff993614c","year":null},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.046489Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:d20dec19b5f3d5a9bc49ec3aca9fa60a6f33aa57aa05aca41d0c1f2447f13175","observation_id":"73bed718-d77c-4933-bf3c-247f5ea976b9","resolution":{"observed_at":"2026-08-11T23:48:26.369936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.249108Z","title":"A.5 Experimental Environments and Computing Resources All the experiments are conducted on a single RTX 3090 with CUDA 11.3","venue":null,"work_id":"303edc6d-0026-4b03-871c-4e3176e8a5a6","year":null},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.053002Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:990024a8d7413917ef915640c5835e65f8a6d3c47c8ac6e09048b791b0ed86b3","observation_id":"aee16219-6655-4fc1-af41-53bbeec654b6","resolution":{"observed_at":"2026-08-11T23:48:26.275524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.230295Z","title":null,"venue":null,"work_id":"6d87227f-29f5-4fe4-ae1a-2b5200d46721","year":null},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.058590Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:d18bf47b8ea7103c6beaab488e51c28aac33a298f61f83dd34a13565130ff7a7","observation_id":"47ce9c14-a9e8-4c0a-a288-acabd25ad61e","resolution":{"observed_at":"2026-08-11T23:48:26.235325Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:48:26.211047Z","title":null,"venue":null,"work_id":"7dfe5038-cceb-4aa6-85c1-0e3ae923e1ef","year":null},"citing_paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T23:48:26.064062Z"},"links":{"citing_paper":"/paper/2412.02225"},"observation_digest":"sha256:8c4a88f65a05846bbb7320fe9996b061ec7c50a45a67b62d61ace55fe600678c","observation_id":"0eac2af9-5aaf-4966-927b-b451a6f69bd0","resolution":{"observed_at":"2026-08-11T23:48:26.217316Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.02225","last_updated":"2024-12-03T07:31:54Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T13:52:40.837972Z","submitted_at":"2024-12-03T07:31:54Z","title":"How to Use Diffusion Priors under Sparse Views?"},"reference_resolution":{"displayed":74,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":63},"total_outbound_references":74},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2412.02225."}