{"as_of":"2026-08-08T08:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:750f5b7421aabd7b08311bcd0fcb829dc477b2a25f3b41b9ea7a76ab625c225b","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:11:31.619541Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.19793/citation-record","integrity":"/paper/2505.19793/integrity","json":"/paper/2505.19793/citation-record.json","paper":"/paper/2505.19793"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:36.130328Z","title":"Large-scale data for multiple-view stereopsis.International Journal of Computer Vision, 120:153–168, 2016","venue":null,"work_id":"8d9654e3-7f53-4895-a4af-9d36568917da","year":2016},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.271130Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:443eb2a27b2d1a9914412dd91d67924ee23c4e3965e2516f34fe2d5e00f02802","observation_id":"ddaba1e4-4907-4949-ad20-a92fc15c41a6","resolution":{"observed_at":"2026-08-07T14:11:36.182436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:27.375001Z","title":"Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.375001Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:362b8c4691caf04c2210502f52c79ae147b6915c23d359f7d5bcb621c7cb53f3","observation_id":"36d03837-1618-48ec-b77a-07c0bca0e616","resolution":{"observed_at":"2026-08-07T14:11:27.375001Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:27.443899Z","title":"Mip-nerf 360: Unbounded anti-aliased neural radiance fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.443899Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:e2c5593ba284f8df174c4fd0cea75645cd57702f56fe5a66b6f0536b2538e34a","observation_id":"1c92216c-6106-418d-9e9d-523b61b3574a","resolution":{"observed_at":"2026-08-07T14:11:27.443899Z","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":"2026-08-07T14:11:35.903924Z","title":"Real-time neural light field on mobile devices","venue":null,"work_id":"8256bf80-590c-451f-ab3a-ef96a78627f1","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.501426Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:8e495dc11a7b85230daddba4f8a6c68fc241c43867851938a89f3a75d42b9f84","observation_id":"f02809ea-f640-4565-8949-14e2388e0fc3","resolution":{"observed_at":"2026-08-07T14:11:36.021742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:35.745154Z","title":"Plenoptic sampling","venue":null,"work_id":"1e7c09fc-effe-4dd0-87c6-615125681754","year":2000},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.565283Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:6b7e9a4efa66314d32728196a007ada882101346c360eef441cf5007833ac489","observation_id":"a1f074e7-11d4-4354-8327-9c6868f949ce","resolution":{"observed_at":"2026-08-07T14:11:35.819282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:27.649504Z","title":"Efficient geometry-aware 3d generative adversarial networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.649504Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:240e91c15be75c676a9d28cebe25f2fadccd87eba0bf2c4ebaf6abd338d41458","observation_id":"b2e985e3-3bd3-40f0-a715-bc557a6d3cbd","resolution":{"observed_at":"2026-08-07T14:11:27.649504Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:27.808877Z","title":"pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.808877Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:4277237645ac20f90e11a78374ba02d15002a527ef920eddd18cddcc52644beb","observation_id":"bff0cf8f-9513-46c8-87a7-b5737df38a93","resolution":{"observed_at":"2026-08-07T14:11:27.808877Z","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":"2026-08-07T14:11:35.596348Z","title":"Mvsnerf: Fast general- izable radiance field reconstruction from multi-view stereo","venue":null,"work_id":"8c4435b9-35f8-4c10-be24-c45be469fa20","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:27.936473Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:96b70d294316ad9978e5584ab073c023aa62eabeb9e7dac3c0fa6cc89754c4c0","observation_id":"525899f8-ec11-4d68-8f67-292adcd34b99","resolution":{"observed_at":"2026-08-07T14:11:35.666114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:28.108405Z","title":"Tensorf: Tensorial radiance fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.108405Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:dcd97c7af4b30d56838569c4ea15a52d55be9cf6248397ad812c913c96b0b649","observation_id":"200f515a-8a5e-41b0-8398-c77911bd5f7c","resolution":{"observed_at":"2026-08-07T14:11:28.108405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12294","last_updated":"2025-08-22T17:46:35Z","snapshot_observed_at":"2026-07-06T15:19:28.033750Z","submitted_at":"2023-04-24T17:46:01Z","title":"Explicit Correspondence Matching for Generalizable Neural Radiance Fields","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12294","snapshot_observed_at":"2026-08-07T14:11:28.260034Z","title":"Explicit correspondence matching for generalizable neural radiance fields.arXiv preprint arXiv:2304.12294, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.260034Z"},"links":{"cited_paper":"/paper/2304.12294","citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:d5e5d0494aca3de6f31a001940bd962b301f49a34c18fa150bd958eb507734bb","observation_id":"621974d1-3c94-4885-b54d-d76aa07b1f40","resolution":{"observed_at":"2026-08-07T14:11:28.260034Z","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":"2026-08-07T14:11:35.458577Z","title":"Mobilenerf: Exploiting the polygon ras- terization pipeline for efficient neural field rendering on mo- bile architectures","venue":null,"work_id":"8a47aa98-2f88-49b9-89f2-7ed1b3b72f87","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.402336Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:eee001bd3e3d2a4f502eadea0e38e49a3be5aff76248dbe6be7b6d79e1d4baac","observation_id":"cec56797-b0d3-42b3-8edf-64ddae76a1d0","resolution":{"observed_at":"2026-08-07T14:11:35.513766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:35.331122Z","title":"Stereo radiance fields (srf): Learning view syn- thesis for sparse views of novel scenes","venue":null,"work_id":"61827f08-3150-4dd6-99ad-4f9fd2c27c95","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.452773Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:1de603cbf89cee2875208e4c180805e13bdc3e726a8f415264449fe17487b666","observation_id":"01443d6e-7189-45c4-ba97-8d15da56b510","resolution":{"observed_at":"2026-08-07T14:11:35.385167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:35.211545Z","title":"Plenoxels: Radiance fields without neural networks","venue":null,"work_id":"0ff42137-f3cb-48f9-9940-8b4bf8598417","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.460914Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:bff2a5c92c61e21cfd323329d719b9d32a09de6128919a4097caf0a990ebaedf","observation_id":"1936c40c-da1d-4096-b0ba-3145477c2aa5","resolution":{"observed_at":"2026-08-07T14:11:35.267725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:35.079247Z","title":"Efficientnerf efficient neural radiance fields","venue":null,"work_id":"8a2d8450-0447-4ec1-8e9c-e67da636c03f","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.564106Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:b3c7acfbddc03e1c62ef8435f8457adddfab40a20672eb3bcc8e9af27e8b5326","observation_id":"b15e20da-6446-42c6-8f04-932ddbfd3826","resolution":{"observed_at":"2026-08-07T14:11:35.156044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.924526Z","title":"Tri-miprf: Tri-mip represen- tation for efficient anti-aliasing neural radiance fields","venue":null,"work_id":"344f4954-01e6-431b-afe5-90b73e7859d3","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.690333Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:bd7981affcb5761a16c01aa104e04da73b5652bb28a2c80ffae8b0dc5a2e063a","observation_id":"320ee482-078c-4003-8850-bfb91ef280c6","resolution":{"observed_at":"2026-08-07T14:11:34.997467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.822398Z","title":"Geonerf: Generalizing nerf with geometry priors","venue":null,"work_id":"1b5a94e6-cc39-405c-a5be-023f0a1442ba","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.836867Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:791947fa9f82dcca1a4c5f57886ca25166be3e964ee511d7a36492f42b41d640","observation_id":"e1a45aff-4866-4535-b2f0-4a97a1fd380d","resolution":{"observed_at":"2026-08-07T14:11:34.873041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.709240Z","title":"Relu fields: The little non-linearity that could","venue":null,"work_id":"573cc8f2-5bfc-4d3a-9cd3-9b0d8632431b","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:28.991999Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:5a5ee44fe20d1d29a84abd4ea3f6ed63f451925bbcd10aed2d2f9073301415ad","observation_id":"eef90748-d65a-430e-864c-bacd967acb5d","resolution":{"observed_at":"2026-08-07T14:11:34.763012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:29.144482Z","title":"3d gaussian splatting for real-time radiance field rendering.ACM Trans","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.144482Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:22a7d8968485a022b96a63fb9e9abf613bf018a360e07753749c129b6e1f7bde","observation_id":"be75772d-86ec-4560-9eda-db5c3841b7b8","resolution":{"observed_at":"2026-08-07T14:11:29.144482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-07T14:11:29.303087Z","title":"Adam: A method for stochastic opti- mization.arXiv preprint arXiv:1412.6980, 2014","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.303087Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:0d2e62edfa336b16435a1b42970b2be610abd6e3da8f633c9f98d6d90b731827","observation_id":"551074cd-aa8c-4255-befb-ae1000ada0f4","resolution":{"observed_at":"2026-08-07T14:11:29.303087Z","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":"2026-08-07T14:11:34.584670Z","title":"Adanerf: Adaptive sam- pling for real-time rendering of neural radiance fields","venue":null,"work_id":"fc42e26a-307e-4fd6-90df-f0b8362ed924","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.423260Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:93a83530fcc2570afa30b560ebb057114d198fa6a9cdf8e8a369a7ae6164468f","observation_id":"29b93be3-ec4a-4898-b5c6-e87f8bf6873d","resolution":{"observed_at":"2026-08-07T14:11:34.642778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.522588Z","title":"Mine: Towards continuous depth mpi with nerf for novel view synthesis","venue":null,"work_id":"01295d7b-f074-4c55-b762-16cca74d3637","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.542350Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:01b0843b6a4b2868a08e974df0da511e0c0549366f0336af80bcf6cfc62935c1","observation_id":"da8a438d-e388-42a6-991a-918e02452d7e","resolution":{"observed_at":"2026-08-07T14:11:34.553335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.408237Z","title":"Efficient neural radiance fields for interactive free-viewpoint video","venue":null,"work_id":"6f9b5213-98f2-466e-b637-4b869a45315d","year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.672393Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:29bd8fa7f73bc4d552e740959831f11b87c6f8f62db00013f806b5c8fdf258ea","observation_id":"82140f17-6e1f-4a66-ae18-a0db07de8d92","resolution":{"observed_at":"2026-08-07T14:11:34.468243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:29.822864Z","title":"Neural sparse voxel fields.Advances in Neural Information Processing Systems, 33:15651–15663,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.822864Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:5cde5fc3e3d7d8eeff1e71ae78d9a45c27167a60d75662314043d033cab23230","observation_id":"06fb60df-2a3a-485f-bcf3-888d6789acca","resolution":{"observed_at":"2026-08-07T14:11:29.822864Z","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":"2026-08-07T14:11:34.291123Z","title":"Mvsgaussian: Fast generalizable gaussian splatting recon- struction from multi-view stereo","venue":null,"work_id":"a0eb604f-e1f4-4267-8c34-cd7757db3bb0","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:29.922621Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:f8db955564dfbfecc08e378576b4520e00946874e912cba753023185cb1292d0","observation_id":"7f84ab1e-0324-46f6-a8b8-ea3504ab5e34","resolution":{"observed_at":"2026-08-07T14:11:34.352448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.164119Z","title":"Geometry-aware reconstruc- tion and fusion-refined rendering for generalizable neural ra- diance fields","venue":null,"work_id":"0f408b6e-cb27-4e41-9b59-7aab5c67f865","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.067761Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:5d6c5ab7fac91471e56bb4b5231f5a80542161b816ad2b15aa9036b9a35882bf","observation_id":"2c099f60-4a08-46f4-978b-2187b938152b","resolution":{"observed_at":"2026-08-07T14:11:34.233613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:34.019498Z","title":"Neural rays for occlusion-aware image-based render- ing","venue":null,"work_id":"1e6cc842-fa10-4354-8bd7-089788f8e91e","year":null},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.223460Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:23ae4eeb0abb782892d08556d61290ba7ddc7e02145b769a0bfc9fb609bfe2a8","observation_id":"75630994-07dd-4744-b3a7-7ddf5905f5f1","resolution":{"observed_at":"2026-08-07T14:11:34.109620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:33.914668Z","title":"Local light field fusion: Practical view syn- thesis with prescriptive sampling guidelines.ACM Transac- tions on Graphics (ToG), 38(4):1–14, 2019","venue":null,"work_id":"a4fea531-6451-4964-a662-8f0ba475d2dd","year":2019},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.348518Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:89396f241a49be52eb3489fe470d7c9fc4a249dc65b054827f6e7c2d4b8cb291","observation_id":"da2a5cab-12b0-4bb6-a66c-d6f089f240c4","resolution":{"observed_at":"2026-08-07T14:11:33.954930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:33.778241Z","title":"Srinivasan, Matthew Tancik, Jonathan T","venue":null,"work_id":"0105f75d-d8cd-4160-9a51-391956875f89","year":2020},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.458939Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:a655051215dc3aa0cea709d7a2f57341909dcec94568cec71128afd3227ba226","observation_id":"81612f9b-c2ae-4a7d-b4b6-2f136099a8d7","resolution":{"observed_at":"2026-08-07T14:11:33.828718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:30.528312Z","title":"Instant neural graphics primitives with a mul- tiresolution hash encoding.ACM transactions on graphics (TOG), 41(4):1–15, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.528312Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:35c8ad50f7202e528d08623a2134b2441e1dc2a39a89255ba6f46970c7856a68","observation_id":"0755c1fb-2a4a-45f9-91be-2bb38201062b","resolution":{"observed_at":"2026-08-07T14:11:30.528312Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:30.604877Z","title":"Donerf: Towards real- time rendering of compact neural radiance fields using depth oracle networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.604877Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:ac2da5772c37248852edc72391159edd13f47dbf07c0e23acfa09afe37958fd7","observation_id":"147e1d48-4980-4059-ba2c-46521d2ec144","resolution":{"observed_at":"2026-08-07T14:11:30.604877Z","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":"2026-08-07T14:11:33.493287Z","title":"Cascaded and generalizable neural ra- diance fields for fast view synthesis.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023","venue":null,"work_id":"8e13a605-db84-42d9-9643-e1a4e40571e3","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.697608Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:bb5794fc32f2d72058fe23729483775dc2433f53d13311ee1f3e76d50520533b","observation_id":"82d2aace-a32a-46d1-8274-c6549fda26c1","resolution":{"observed_at":"2026-08-07T14:11:33.555347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.04586","last_updated":"2024-08-08T16:56:03Z","snapshot_observed_at":"2026-07-06T18:58:30.942582Z","submitted_at":"2024-08-08T16:56:03Z","title":"Sampling for View Synthesis: From Local Light Field Fusion to Neural Radiance Fields and Beyond","version":1},"cited_work":{"arxiv_id":"2408.04586","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.04586","snapshot_observed_at":"2026-08-07T14:11:31.717753Z","title":"Sampling for View Synthesis: From Local Light Field Fusion to Neural Radiance Fields and Beyond","venue":"cs.GR","work_id":"19c7c61e-a54a-49dc-83b8-974b70e93d41","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.726440Z"},"links":{"cited_paper":"/paper/2408.04586","citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:6e377cc47f5fbb7e68218f8dcd99c3631af4d5aeb0d863389b119c81a0c2d0bf","observation_id":"f088c664-2d6e-4ca0-9932-c73b4d86ecc6","resolution":{"observed_at":"2026-08-07T14:11:31.772287Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:30.791698Z","title":"Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.791698Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:de1faa2aeb8d296fb1b7ca235bec3dcaa5ac0ae9ae322f2ccc8df04921691064","observation_id":"e33e1f5d-6ad5-4619-b338-16d57d65ece7","resolution":{"observed_at":"2026-08-07T14:11:30.791698Z","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":"2026-08-07T14:11:33.336988Z","title":"Recent advances in im- plicit representation-based 3d shape generation.Visual Intel- ligence, 2(1):9, 2024","venue":null,"work_id":"bd495d0e-5f26-441d-bf92-7254abb7c21c","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.862820Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:b7e4d3903e6e95173e4a2958db5b4c4c4fdc67dae6a1ba800618d5980e991ca1","observation_id":"bb4b612b-7d83-4789-9cd9-515da568a9e5","resolution":{"observed_at":"2026-08-07T14:11:33.410200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:33.137842Z","title":"Splatter image: Ultra-fast single-view 3d recon- struction","venue":null,"work_id":"fcebef6d-eb13-4db3-b4f9-3ee8e1331ac4","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.929687Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:1a2d456b1e2df8b97ba0c5b0e3eeec907782e3b6c773b8696347276590a5e138","observation_id":"31c019c7-7293-4703-9796-ff30feee885c","resolution":{"observed_at":"2026-08-07T14:11:33.219651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.946627Z","title":"Global latent neu- ral rendering","venue":null,"work_id":"d0d5e28c-81df-4cd0-8b20-1bd5370a0d98","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.999631Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:f843097e3161a3aabf306385d040ff9ed39122de19c140ea93b4db1e99808c2e","observation_id":"ce72235d-582e-4e75-a38f-593877fc40cb","resolution":{"observed_at":"2026-08-07T14:11:33.035643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.740722Z","title":"Grf: Learning a general radi- ance field for 3d representation and rendering","venue":null,"work_id":"c7f3202c-8808-4b47-84ef-46ca4ecc091f","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.079551Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:66d3e68ea1dd6677057103976cbdcd66e3b68d275c73a7fe619ca11d478d40fa","observation_id":"ad4580f7-67be-4942-888a-589fb4d1daf8","resolution":{"observed_at":"2026-08-07T14:11:32.854343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.590140Z","title":"Learning neural duplex ra- diance fields for real-time view synthesis","venue":null,"work_id":"f12044a7-f387-479e-a020-c02546154b18","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.137232Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:898c6dc088c647f66894453f008b862392b3d84250b1e476d0ef8af523512152","observation_id":"22478969-2fb4-409b-8b4c-f06c4d4c6dda","resolution":{"observed_at":"2026-08-07T14:11:32.665701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.430800Z","title":"Is attention all that nerf needs?Proceedings of the International Conference on Learning Representations (ICLR), 2023","venue":null,"work_id":"6063ac30-ad3e-4802-8482-b3a8b8ef0511","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.214884Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:80d93c9f5d8dad64aa6edcee411f870c12ac43efd3166becf969154aa16e2433","observation_id":"85f76194-067c-4aba-bf34-94014af8ee4f","resolution":{"observed_at":"2026-08-07T14:11:32.503946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.284391Z","title":"Ibr- net: Learning multi-view image-based rendering","venue":null,"work_id":"4fcdd0ca-7e7e-4aa8-8ca1-22bdf56db8c3","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.262625Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:94382621c61b7287d594bec4bb1aa3ecd6b70b9cfb274c58af2f53820fc174f8","observation_id":"4be86da7-9863-4501-8a42-0748c703446f","resolution":{"observed_at":"2026-08-07T14:11:32.345064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:31.333925Z","title":"Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.333925Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:1d273d2385edbd5d176d07870ee833da6e1f0d885922a8930da720c1074cd1ff","observation_id":"11c95e76-a1ed-4979-a442-364dcac178cc","resolution":{"observed_at":"2026-08-07T14:11:31.333925Z","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":"2026-08-07T14:11:32.171971Z","title":"Adaptive shells for efficient neu- ral radiance field rendering.ACM Transactions on Graphics (TOG), 42(6):1–15, 2023","venue":null,"work_id":"5a6d8847-d44f-4f56-8189-11573c162626","year":2023},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.381851Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:76839eba89cdd374d361d35906e4704afd178350f4484e8b194cca791ca374dd","observation_id":"ac935623-b47a-4b8d-b69c-e8b91ce884b6","resolution":{"observed_at":"2026-08-07T14:11:32.210832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:32.038166Z","title":"Murf: Multi-baseline radiance fields","venue":null,"work_id":"a16bdd46-7ed1-4c6d-96eb-49b98160f7e4","year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.440729Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:415a445ebbdc5e2652a0481f35e28466443e9cd92e8b8ffa06efb4d87c69233d","observation_id":"00333b9b-d1d8-491f-84cd-45242fb93577","resolution":{"observed_at":"2026-08-07T14:11:32.092671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:31.485975Z","title":"Plenoctrees for real-time rendering of neural radiance fields","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.485975Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:23b8b6e60d2f051e965a1f3c94f243059f77af42141560ffc739ea66aa5767be","observation_id":"99f8f719-4983-4fea-8e1a-9692d6d8cdb5","resolution":{"observed_at":"2026-08-07T14:11:31.485975Z","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":"2026-08-07T14:11:31.872656Z","title":"pixelnerf: Neural radiance fields from one or few images","venue":null,"work_id":"d3f7b440-ffc1-436d-91a1-115474a55a6f","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.528714Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:9a24330fb9608ba8817afd37aa2ff5620ad7359bd38b8ff8021967f7947fafe6","observation_id":"17250589-82f6-4396-91be-ab5bf34fd352","resolution":{"observed_at":"2026-08-07T14:11:31.927244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T14:11:31.573164Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.573164Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:21fbffec5ce27a3892bcaee4db38061a60fc522fb3fa8177ca984cb39d4413c6","observation_id":"f998e05d-5fc8-4871-befc-0d9cfba38122","resolution":{"observed_at":"2026-08-07T14:11:31.573164Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:11:31.619541Z","title":"Gps- gaussian: Generalizable pixel-wise 3d gaussian splatting for real-time human novel view synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:31.619541Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:c874354bd743c15648a6e007a67d6c3067976e7bba07b62ea41b5bb1a1e76cb2","observation_id":"62f9d90d-21bb-4b0a-bb75-b8ce43dc2f0b","resolution":{"observed_at":"2026-08-07T14:11:31.619541Z","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":"2026-08-07T14:11:33.631127Z","title":null,"venue":null,"work_id":"c383fd51-64b2-4d8b-847f-e89ca95949e5","year":2021},"citing_paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T14:11:30.657847Z"},"links":{"citing_paper":"/paper/2505.19793"},"observation_digest":"sha256:551b00ffbaf735d3894098bf912f519285777aa3a73b518fb0f5a9f859186ee2","observation_id":"3b01fe6b-6019-40c1-9d1d-a205315f9d00","resolution":{"observed_at":"2026-08-07T14:11:33.707654Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.19793","last_updated":"2025-05-26T10:23:59Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T14:03:58.564343Z","submitted_at":"2025-05-26T10:23:59Z","title":"Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":1,"verified_fuzzy":30},"total_outbound_references":48},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2505.19793."}