{"as_of":"2026-08-20T05:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fccd49f520e588efa2628d58d834243f0e2894f58c913c901eecad384b4078a7","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T13:16:55.366759Z","state":"measured"},{"denominator":61,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":61,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T20:19:13.643985Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-15T13:55:53.211660Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07289","snapshot_observed_at":"2026-08-15T20:19:13.643985Z","title":"Learning inverse laplacian pyramid for progressive depth completion.arXiv preprint arXiv:2502.07289, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.13279","last_updated":"2025-05-20T07:45:25Z","snapshot_observed_at":"2026-08-17T00:27:09.124333Z","submitted_at":"2025-05-19T16:02:37Z","title":"Event-Driven Dynamic Scene Depth Completion","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-15T20:19:13.643985Z"},"links":{"cited_paper":"/paper/2502.07289","citing_paper":"/paper/2505.13279"},"observation_digest":"sha256:ef63a57c2a12d2e93ef843bf2f1db968134367e522fdbbf0f12dac5c36068b34","observation_id":"26d0614a-9d5b-4469-9369-5003e5b45a52","resolution":{"observed_at":"2026-08-15T20:19:13.643985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"cited_work":{"arxiv_id":"2502.07289","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.07289","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","venue":null,"work_id":"ae3ba513-687f-46f9-8a8a-43c8d410a584","year":2025},"citing_paper":{"arxiv_id":"2603.10584","last_updated":"2026-05-02T12:44:50Z","snapshot_observed_at":"2026-08-12T17:50:29.016737Z","submitted_at":"2026-03-11T09:40:03Z","title":"Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-15T13:52:01.152288Z"},"links":{"cited_paper":"/paper/2502.07289","citing_paper":"/paper/2603.10584"},"observation_digest":"sha256:18af1cb5d5d3e4cd26b60d159cf1c79308760b66ba3b99ba8d468463d3e7bac8","observation_id":"5db3ed3a-644d-4a0b-80c9-36b038b2e7a2","resolution":{"observed_at":"2026-05-15T13:55:53.213639Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.07289/citation-record","integrity":"/paper/2502.07289/integrity","json":"/paper/2502.07289/citation-record.json","paper":"/paper/2502.07289"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T13:16:56.322689Z","title":"Hybrid-mvs: Robust multi-view reconstruction with hybrid optimization of visual and depth cues,","venue":null,"work_id":"1aa976e2-207a-4017-baf4-56d4eae1b8c2","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.067902Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:8c6f41b96332d89d8d42ca5e6b464f677396154941b2d6b69bc4f7281df5e57c","observation_id":"3ddd7308-714e-42cb-8f92-67c3e4474d14","resolution":{"observed_at":"2026-08-08T13:16:56.328219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.307125Z","title":"Altnerf: Learning robust neural radiance field via alternating depth-pose optimization,","venue":null,"work_id":"2eb1718e-e58a-492d-a0ed-761641efff49","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.074150Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:c98995e1b7ea29d8f9f3ee43957d2bc1c8aaebccfa05036f13bd4c685afaf31a","observation_id":"016c1a2b-1e10-4ded-9135-04a9463ec950","resolution":{"observed_at":"2026-08-08T13:16:56.312218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.291517Z","title":"A low-cost and scalable framework to build large-scale localization benchmark for augmented reality,","venue":null,"work_id":"4e333175-9ba7-4523-b756-8cef4f511ea6","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.079429Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:a7d93eae645c5c7b1c8a2abd55d279e0445debe7d3da4b3e8993721b4d18c8a0","observation_id":"8f14053d-aebd-4b47-8d68-e1e98d8d5f7f","resolution":{"observed_at":"2026-08-08T13:16:56.296809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.275728Z","title":"Designing for depth perceptions in augmented reality,","venue":null,"work_id":"3cb263ad-5a83-4de6-80a5-138d2be99d83","year":2017},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.084726Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:260193329aa0ab2c1f66a25a5c38c91846524a7271a13cc9131011d74150d481","observation_id":"9dc0f196-55f2-45d3-aac4-423aaff2ea76","resolution":{"observed_at":"2026-08-08T13:16:56.280986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.259359Z","title":"Digital video stabilization method based on periodic jitters of airborne vision of large flapping wing robots,","venue":null,"work_id":"c57ea213-c5d7-4a4a-ba16-daa303d691d3","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.089679Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:7d4f8dcae05c81dacb3fde43057849b9363465595f97021933bc6e68afdd2282","observation_id":"e4195319-7f62-4ef8-b6d1-0ed63728b71e","resolution":{"observed_at":"2026-08-08T13:16:56.264249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.243913Z","title":"Towards real-time monocular depth estimation for robotics: A survey,","venue":null,"work_id":"6fa42041-3645-4e2a-a50f-0c54efa9b9dd","year":2022},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.094674Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:fc6883df955eb5d704ef6a24170b23f7f8855d5ef51534cb3a9efb6ba9d0670d","observation_id":"f2574d3e-0a96-416d-ac2c-bbf757b56552","resolution":{"observed_at":"2026-08-08T13:16:56.249051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.228581Z","title":"Sparse-to- dense depth estimation in videos via high-dimensional tensor voting,","venue":null,"work_id":"d4da1a47-8981-4e8d-bcff-f5849122696f","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.100325Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:7e2c85d646c0f6f5bb479e98c0f62fc15c0246cdba5969492a52c1fdc14c1630","observation_id":"6c6489b3-e638-4646-be45-89aa54e54922","resolution":{"observed_at":"2026-08-08T13:16:56.233788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.212318Z","title":"Dcdepth: Progressive monocular depth estimation in discrete cosine domain,","venue":null,"work_id":"7dadb1c8-7344-47af-94f8-468fc0c28df2","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.105064Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:8fc41e8cecce443eb139760c9e27c1033f0b0c713400a8afaa292b8d7bbd47c9","observation_id":"0175ce54-59d1-4913-9103-c51ca2ad1f42","resolution":{"observed_at":"2026-08-08T13:16:56.218360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.197210Z","title":"Regularizing nighttime weirdness: Efficient self-supervised monocular depth estimation in the dark,","venue":null,"work_id":"4fcaabd7-d6f0-40ba-bae9-a8fe6178ba3c","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.109848Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:3b0069b79f4d5356819916e55a43e7597262ae1eb2052a88889fc5ad09811c9b","observation_id":"2a9d299c-3ed1-47b0-bca0-49b7399162e4","resolution":{"observed_at":"2026-08-08T13:16:56.202179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.181950Z","title":"Depth- centric dehazing and depth-estimation from real-world hazy driving video,","venue":null,"work_id":"9850ee4b-7e61-4ce6-a3c7-c831e64217ac","year":2025},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.114474Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:fa5f12d077400359d0f58a82263e796ed5b345cd42a360968d6b3647caa37086","observation_id":"0a140de4-5cf2-477b-8c5b-f3c9547f1081","resolution":{"observed_at":"2026-08-08T13:16:56.187292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.166243Z","title":"Sgnet: Structure guided network via gradient-frequency awareness for depth map super-resolution,","venue":null,"work_id":"a4d1612a-1420-4465-b2ca-bf5c0d0b4064","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.119159Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:c20b9e3c905a92718a4ff0b79c5b75133c2dc47ddcfc61f89aa8dcc97c7fdc11","observation_id":"1eee76d9-a777-4486-9cc6-f826815d3501","resolution":{"observed_at":"2026-08-08T13:16:56.171389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.119347Z","title":"Deep depth completion of a single rgb-d image,","venue":null,"work_id":"b7b825a2-5785-4489-9f57-5bcf9716f892","year":2018},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.133919Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:40e546968b09267a4e002a7d7524a1d90ab2e5b993db414897864f77456dd0a5","observation_id":"d533f053-2c58-4dca-b2e2-d36ffefaed9c","resolution":{"observed_at":"2026-08-08T13:16:56.124118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.104332Z","title":"Learning depth with convolutional spatial propagation network,","venue":null,"work_id":"eea1b267-b0e4-41e9-86e7-25bb93397279","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.138668Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:8f5d5e0cf27b21415a5e07450ca1a85a57ff64cc522723475f500e79080e2646","observation_id":"1f09fc28-1dda-4b60-b3ff-b5c100d79581","resolution":{"observed_at":"2026-08-08T13:16:56.109458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.089032Z","title":"Non-local spatial propagation network for depth completion,","venue":null,"work_id":"9e389da6-def6-4dfe-a06e-2788f13a3a50","year":2020},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.143505Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:6f879a3dbeced0acc029f291faf20d611435131a2ec4ec1153446b78e3962d80","observation_id":"4dbec7e1-9057-4be4-a786-48e548ae072e","resolution":{"observed_at":"2026-08-08T13:16:56.094029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.058581Z","title":"Rignet: Repetitive image guided network for depth completion,","venue":null,"work_id":"e4fa756e-9f49-496d-ad93-323ca5723554","year":2022},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.152245Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:9457baf0fe4a9e5f800c4369737bbdacf2db0c44e87ee9b2e4833b4b5b355d65","observation_id":"efc0e91f-1985-41c4-b3f2-d435f686a160","resolution":{"observed_at":"2026-08-08T13:16:56.063865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.043613Z","title":"Cspn++: Learning context and resource aware convolutional spatial propagation networks for depth completion,","venue":null,"work_id":"3f31d1a8-ba49-470d-a8a5-95f99119bcf1","year":2020},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.156702Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:87a80ee5d624dc141dfc5ca011a2565c70f127f17df4630e4d090068a8391271","observation_id":"5d0a2357-b46b-430e-ae7d-af25c32395b1","resolution":{"observed_at":"2026-08-08T13:16:56.048742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.028404Z","title":"Dyspn: Learning dy- namic affinity for image-guided depth completion,","venue":null,"work_id":"36612a95-6c7c-4a26-8739-e60889e13b62","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.161520Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:97f2052020f9a6f39c4ba37d76757a7120a169f9dcdef09e088ffa34d1960f55","observation_id":"2b4b3b26-b7eb-4122-9858-a040e5bac518","resolution":{"observed_at":"2026-08-08T13:16:56.033295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.150900Z","title":"Depth seeds: Recovering incomplete depth data using superpixels,","venue":null,"work_id":"f3e9a349-e0c7-479f-8738-d8cf2b66b12c","year":2013},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.165975Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:707dc580f319dff6c274b7fd885f9d98962a2c8b73ae7a1e6090bb02d9049997","observation_id":"89c02ff8-6de8-403d-82fe-bf0eb4033c85","resolution":{"observed_at":"2026-08-08T13:16:56.155808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.013070Z","title":"Seeds: Superpixels extracted via energy-driven sampling,","venue":null,"work_id":"14147cd2-f139-48f9-b982-43782f3ed78d","year":2015},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.170330Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:353d6ef59017ae5fb847bd813bd3ffe0ea2c1ca0f607c1ebc710916e409624f8","observation_id":"ef8c9ab4-6631-4244-a2e6-b5632fa2cdab","resolution":{"observed_at":"2026-08-08T13:16:56.018172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.134832Z","title":"In defense of classical image processing: Fast depth completion on the cpu,","venue":null,"work_id":"278cc484-f5b4-402b-bbe4-2a62041fa3ea","year":2018},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.175662Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:658660c2e5670de55b6f9114e7780dc6ba66a22f314e8cef12e21e5cdba27d61","observation_id":"e5a4023c-e733-4fba-bb28-d890eb2745d4","resolution":{"observed_at":"2026-08-08T13:16:56.140012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.997791Z","title":"A surface geometry model for lidar depth completion,","venue":null,"work_id":"91e52e0d-3315-41e7-9dbc-3639d6712f01","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.180279Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:e5bfbe3672d2152f5c288ef63ec9591e4071eca9e00678e7079f48b48fbec875","observation_id":"8d0bce8f-1cae-48c4-ab39-4c42d5b93d71","resolution":{"observed_at":"2026-08-08T13:16:56.002758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.982152Z","title":"Sparsity invariant cnns,","venue":null,"work_id":"95d24c2c-2712-4a61-9c0d-8012563a23cf","year":2017},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.184768Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:81c9c1c32a84b25c2e947d38c4db253f6fc159261433333414bc45da5c687d55","observation_id":"eb9e6761-33db-45a6-837b-d96a57522126","resolution":{"observed_at":"2026-08-08T13:16:55.987109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.966041Z","title":"Hms- net: Hierarchical multi-scale sparsity-invariant network for sparse depth completion,","venue":null,"work_id":"1adc80bc-250c-407b-b48f-458e7153e824","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.189819Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:b2f71d1643d5d4900734b891f8f91ebf2b4de1e42b9ae80e8139103f4205ee99","observation_id":"0ee62c98-6a6b-42ba-8692-688824a9c163","resolution":{"observed_at":"2026-08-08T13:16:55.971270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.948949Z","title":"Uncertainty- aware cnns for depth completion: Uncertainty from beginning to end,","venue":null,"work_id":"93e2859c-8f30-4b33-90cb-471bf81dbc41","year":2020},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.194851Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:4d7cf061d2407770fe157677df7c2bea1488450631b3e6d4f3f28d77e9150a9a","observation_id":"a532d2d0-cad1-4550-aa8a-2de04ec0bbfd","resolution":{"observed_at":"2026-08-08T13:16:55.955154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.932302Z","title":"Estimat- ing depth from rgb and sparse sensing,","venue":null,"work_id":"a81d1f36-f60e-4508-97da-a51441e982f7","year":2018},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.199617Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:59b5107fe3c8678de5d874166f324a4889c214fe24db343723bb9bdcd8e82ecf","observation_id":"acf3bb9e-c067-4f3d-b4a6-6dda013f47b3","resolution":{"observed_at":"2026-08-08T13:16:55.937937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.916279Z","title":"Learning steering kernels for guided depth completion,","venue":null,"work_id":"7b9f9a54-e497-4a33-92a3-a6d2ced5b574","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.204967Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:186ca67461988d77338fd2d0d2ecaa0ffadc03c3b17214b3f7368308e250904f","observation_id":"943c8196-ed0b-4f96-bda7-d96c7e48cc03","resolution":{"observed_at":"2026-08-08T13:16:55.921638Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.900364Z","title":"Bilateral propagation network for depth completion,","venue":null,"work_id":"a8dfa4fa-7c3f-4777-b64a-71e8bfb90c85","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.209563Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:81008086088b183c00f46a341c4299bac35b93e693854cd361a25240f5239263","observation_id":"8c707a89-2170-4971-b072-65e1aa0946e4","resolution":{"observed_at":"2026-08-08T13:16:55.905631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.883945Z","title":"Learning joint 2d- 3d representations for depth completion,","venue":null,"work_id":"cdad1799-e006-448c-a5df-ac6adf4c9453","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.214224Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:2d28dab357f7292d4d8df54cdc33ef9de85ae32c99d198b574c8ad9f6998628c","observation_id":"5ab22e4f-ea1d-4fc6-b8c5-43a12f4ecbc9","resolution":{"observed_at":"2026-08-08T13:16:55.889275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.868357Z","title":"Deeplidar: Deep surface normal guided depth prediction for outdoor scene from sparse lidar data and single color image,","venue":null,"work_id":"834c6771-1fcc-490d-b578-0f3e500e4528","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.218862Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:f424ed0dc57c9ceb482034ece995665e431749994ac54ed445f5b7cc3710128a","observation_id":"9e4740b1-8f1e-43b0-ba9a-686e5ce030c3","resolution":{"observed_at":"2026-08-08T13:16:55.873612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.851937Z","title":"Learning guided convolutional network for depth completion,","venue":null,"work_id":"bf724ed5-5c43-48bc-b130-6024b79fe0d6","year":2020},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.223471Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:026a190f55c4798c4728c31b117584579986bc0f7006b6b653956fb3b4666fe3","observation_id":"56b7d4d9-447b-4400-a284-85ba6c4c619f","resolution":{"observed_at":"2026-08-08T13:16:55.857472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.832356Z","title":"Guideformer: Transformers for image guided depth completion,","venue":null,"work_id":"48f35fd1-0670-40b6-92de-3a5afbb41259","year":2022},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.228254Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:9139eaa3e432e1ffea93e12efa0f0c334e518fe60028cb705339eecc5627cff2","observation_id":"29f20205-7d10-4fc7-aa09-ef849bb2d8b3","resolution":{"observed_at":"2026-08-08T13:16:55.838859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.813767Z","title":"Bev@dc: Bird’s-eye view assisted training for depth completion,","venue":null,"work_id":"fdde86d0-4a9a-4ca2-bcbf-3e050616acb5","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.233165Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:5a4187590e4ea5673711669414aedf8d87da0b72e5b21205cc346652b414931a","observation_id":"1c699943-abca-4c12-b600-b0fa89df38e1","resolution":{"observed_at":"2026-08-08T13:16:55.819532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.796391Z","title":"Tri-perspective view decomposition for geometry-aware depth completion,","venue":null,"work_id":"b5ed1ae9-95d0-4d71-a077-e27c80c9868b","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.238315Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:2ba86f8fc85d0126dddf34ea93a268327abb6e4893f23eb5f1a962f1214ae2b0","observation_id":"317cd449-3501-4c10-b5a6-cdc58bff34c3","resolution":{"observed_at":"2026-08-08T13:16:55.802515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.779692Z","title":"Dynamic spatial propagation network for depth completion,","venue":null,"work_id":"477e947f-9bb1-4a7e-9e9b-0e91110d19f6","year":2022},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.243865Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:7289a40c4252be950adb3e6f5d47112acdeb693764105320932b112844b07df5","observation_id":"e142d01f-d3f2-415f-a011-456301cbd564","resolution":{"observed_at":"2026-08-08T13:16:55.784966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.763478Z","title":"Graphcspn: Geometry- aware depth completion via dynamic gcns,","venue":null,"work_id":"9ffa84bc-be14-4eec-8c01-7681062556b4","year":2022},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.248780Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:5574b841e620b9951589261b45ec40dba53ca253931eaf23c60c9708fe5a546e","observation_id":"8f9bef56-e8ae-40a9-9f30-a5dc599fc42c","resolution":{"observed_at":"2026-08-08T13:16:55.768896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.746471Z","title":"Lrru: Long- short range recurrent updating networks for depth completion,","venue":null,"work_id":"2a67cd5a-4367-448b-b4d8-112dac24bf0e","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.253377Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:cda59c994ba5e9879a87502c558cb1c60732cf1599681b8a9a42f103423f9c22","observation_id":"0bed2f6d-d5c7-45e5-83cc-58d23bc7a4f4","resolution":{"observed_at":"2026-08-08T13:16:55.752063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.258484Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.258484Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:fb13bcb0b72a48bb8ff9ef70822a57b1ba9103aaedd61f9d1c0c70d2b7a454b7","observation_id":"5f85e94d-59a9-4d17-a66a-20085aa56c32","resolution":{"observed_at":"2026-08-08T13:16:55.258484Z","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":"2026-08-08T13:16:55.262938Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.262938Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:4e41d41f4959f31c10af4e629ec06d9b6951fc04cc7ca16b6e76129695c740bb","observation_id":"a1dee641-a4bd-439e-a6f0-e83d0e94523e","resolution":{"observed_at":"2026-08-08T13:16:55.262938Z","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":"2026-08-08T13:16:55.709920Z","title":"Improving depth completion via depth feature upsampling,","venue":null,"work_id":"dd3346ee-0834-4605-99d0-0014bb456e24","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.267719Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:3d05dcc5143e996150749444c5a09a26544a3b5f7708681979a5d42abf36e27e","observation_id":"456a9257-d3bb-41f5-b4a7-237911442bd4","resolution":{"observed_at":"2026-08-08T13:16:55.714914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.694573Z","title":"Deformable convolutional networks,","venue":null,"work_id":"89390997-5c1a-462f-af0e-02f667cef737","year":2017},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.272526Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:9fd6e4bab3171f47f891d94b5e6017254e48c4f91beea89a2b2d2bbcf0398120","observation_id":"48c9af89-65d8-4ede-b7b3-2af10bbb7c51","resolution":{"observed_at":"2026-08-08T13:16:55.699369Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.678120Z","title":"Deformable convnets v2: More deformable, better results,","venue":null,"work_id":"2656e2b6-2d72-4a69-bb2f-cba15f74fbb8","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.277345Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:38506526670be07852836400c518a3b1552f90591b8e59999a6cc521a89e3dfd","observation_id":"5bb473d6-3993-4fb7-85b4-783f34e78523","resolution":{"observed_at":"2026-08-08T13:16:55.683776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.662884Z","title":"Sparse-to-dense: Depth prediction from sparse depth samples and a single image,","venue":null,"work_id":"15b0468d-e18b-4406-a986-d8c230d557bf","year":2018},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.282146Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:33b372172fb1111f02382064bba4f69d7c1a9021c4f8674ae56285c1631c977c","observation_id":"8030c225-69af-4868-9535-07182a300534","resolution":{"observed_at":"2026-08-08T13:16:55.668113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.646951Z","title":"Confidence propagation through cnns for guided sparse depth regression,","venue":null,"work_id":"ba506b07-f547-4c63-af84-351d3f8bf849","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.287086Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:ac0e61399a43590d2ff926a92848e39796f4425fc8309d189aec23b9c61522b5","observation_id":"15406925-986f-4118-96d7-0824f6c3d8ee","resolution":{"observed_at":"2026-08-08T13:16:55.652079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.629741Z","title":"Depth completion with twin surface extrapolation at occlusion boundaries,","venue":null,"work_id":"fa2b1682-3f98-4cca-9074-0753bdcf9728","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.291963Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:5f739f972907ce609bb782aa38261cbc3eccffeca6c81472a09655f13b8c19a8","observation_id":"9ab69975-f163-4343-8115-cbdb77237403","resolution":{"observed_at":"2026-08-08T13:16:55.634845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.613793Z","title":"Adaptive context-aware multi- modal network for depth completion,","venue":null,"work_id":"a6aa355a-e10b-465e-be03-de8bda8e3cac","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.296732Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:4f114b89a20700e6a1459aec6bf0c77e7d7d08d9a026dfae8ffd2961c89d818e","observation_id":"3f960fa1-1661-4dba-9e12-15a61ccefb3a","resolution":{"observed_at":"2026-08-08T13:16:55.618744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.597568Z","title":"Fcfr-net: Feature fusion based coarse-to-fine residual learning for depth completion,","venue":null,"work_id":"937df41b-49fb-4085-ba46-4e040e1cbaed","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.301698Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:3ab0da8bbc9dd119a9b6e0cb7159219471e4ca84e3e0e6ece0ac8163d394f262","observation_id":"0ef5b65d-6672-4a15-8686-3dea638109e1","resolution":{"observed_at":"2026-08-08T13:16:55.603028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.579686Z","title":"Penet: Towards precise and efficient image guided depth completion,","venue":null,"work_id":"dc333904-50dc-4b4c-b539-4c71966c5a3d","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.307262Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:1f2f98d99b1ffeecee214e007a9c850df5b6479ec1d8e84dd0beaf3276768f24","observation_id":"53b3c897-ee2c-4b68-a032-0bc610f833b3","resolution":{"observed_at":"2026-08-08T13:16:55.585674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.562314Z","title":"Completionformer: Depth completion with convolutions and vision transformers,","venue":null,"work_id":"54648e8c-5a6c-4995-884f-ef771c754450","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.312686Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:52eaf6ce923f386a7090364f705db1639eb8f8a48b3cf58fcd88256e6a438ecd","observation_id":"6b4c8ddf-1919-4d00-934b-72e5a14b13bd","resolution":{"observed_at":"2026-08-08T13:16:55.567757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:56.074172Z","title":"Decomposed guided dynamic filters for efficient rgb-guided depth completion,","venue":null,"work_id":"31ea3aef-067c-41f8-9bfb-dd7d3c16cc03","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.317526Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:c351997b3aa8288ece99816b94d659af23b10e0f813312bc859d8406724caed6","observation_id":"406a8b62-542a-4637-a936-995679991588","resolution":{"observed_at":"2026-08-08T13:16:56.079102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.543756Z","title":"Ogni-dc: Robust depth completion with optimization-guided neural iterations,","venue":null,"work_id":"9661e6e0-0c09-4051-a8c0-d0361f089990","year":2024},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.322096Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:71fc792a43ada71c4a0070925cd349fed4bb3ab983ce2699bca3685307512cce","observation_id":"5a034338-1775-4a2d-8656-c8bfab5ecfc1","resolution":{"observed_at":"2026-08-08T13:16:55.550518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.526790Z","title":"Are we ready for autonomous driving? the kitti vision benchmark suite,","venue":null,"work_id":"c08349b1-50f1-4e3d-b80d-83bf39ffcea9","year":2012},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.327097Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:4664235fbeb4bb5f5b53cb65eeded49af67e0078059f9297b7da6f1cad67827e","observation_id":"c333efdd-0976-45d4-a898-2cb09bb1e4cb","resolution":{"observed_at":"2026-08-08T13:16:55.532201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.509909Z","title":"Indoor segmentation and support inference from rgbd images,","venue":null,"work_id":"2123883d-180d-4dee-9912-ad9fa565fd1f","year":2012},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.331723Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:02d97633e0cd70803e8b703b20d74552ae5392cc0d4ac0c16f642f5bf02cfd4d","observation_id":"d77012fc-56d7-4263-a2f3-af508d876f51","resolution":{"observed_at":"2026-08-08T13:16:55.515646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.493044Z","title":"Pytorch: An imperative style, high-performance deep learning library,","venue":null,"work_id":"ab56c2d6-f1e9-41b3-a99a-eea94fe2f543","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.336918Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:3ce870b0fd736b3ec2deb1b130e4ee6d46d6920c0d7d9b1ab4c2affcc1172940","observation_id":"5cf48079-a2be-4532-a9c9-d9aa580474a9","resolution":{"observed_at":"2026-08-08T13:16:55.498483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.07648","last_updated":"2017-05-26T18:53:56Z","snapshot_observed_at":"2026-08-17T00:23:43.437016Z","submitted_at":"2016-05-24T20:28:53Z","title":"FractalNet: Ultra-Deep Neural Networks without Residuals","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.07648","snapshot_observed_at":"2026-08-08T13:16:55.341820Z","title":"Fractalnet: Ultra-deep neural networks without residuals,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.341820Z"},"links":{"cited_paper":"/paper/1605.07648","citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:0267582bf95bc50d4f9a16223ce21ab7c1052bac6876a855d9fef3830e418e40","observation_id":"19a0e87a-c676-4eb3-9b44-ac0e077c04e1","resolution":{"observed_at":"2026-08-08T13:16:55.341820Z","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":"2026-08-08T13:16:55.346963Z","title":"Decoupled weight decay regularization,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.346963Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:778a25343a3f107ea0ee6131d9f49c06f4faa34ecad3dda9c844aab664ab6715","observation_id":"02f55804-d1f3-4ba4-acdb-c6a5a2385d99","resolution":{"observed_at":"2026-08-08T13:16:55.346963Z","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":"2026-08-08T13:16:55.351586Z","title":"Super-convergence: Very fast training of neural networks using large learning rates,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.351586Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:a0efbd121dd37e10444615f5fb985c16e809a8f01f9540f4770cef2908bbf4d0","observation_id":"ffd7635d-88c4-49c5-993a-67fdaa6798a8","resolution":{"observed_at":"2026-08-08T13:16:55.351586Z","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":"2026-08-08T13:16:55.454325Z","title":"Aggregating feature point cloud for depth completion,","venue":null,"work_id":"ddf76a8d-7e6b-4ac9-a921-fb3767e0b16e","year":2023},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.357145Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:1e99562429b21f12ea1cb0fad8d93fd774d5e6b02df6658789265f7c62dad7c5","observation_id":"21ae7623-f06c-4487-9790-fe7b4a3ce842","resolution":{"observed_at":"2026-08-08T13:16:55.460191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.437904Z","title":"Sparse and noisy lidar completion with rgb guidance and uncertainty,","venue":null,"work_id":"b335ba60-e145-4db8-8beb-68ceb9f5358c","year":2019},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.361656Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:9d9973a5cef2e963e2dfac5f1176fb051923e8ef688385b3f9e27767d777a2e5","observation_id":"8930fd33-63da-4a86-8a4c-493996bfad17","resolution":{"observed_at":"2026-08-08T13:16:55.443014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-08T13:16:55.418442Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":"1bdfab33-3029-476c-8051-30255349e708","year":2021},"citing_paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-08T13:16:55.366759Z"},"links":{"citing_paper":"/paper/2502.07289"},"observation_digest":"sha256:913e2e9aaeb82fa542eb9b425c0336fe6d8ba8f01851798901053af661ccabd4","observation_id":"44b21de9-a2ef-458a-b311-faf60677f8d6","resolution":{"observed_at":"2026-08-08T13:16:55.425439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.07289","last_updated":"2025-02-11T06:21:42Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T09:00:15.435501Z","submitted_at":"2025-02-11T06:21:42Z","title":"Learning Inverse Laplacian Pyramid for Progressive Depth Completion"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":54},"total_outbound_references":59},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2502.07289."}