{"as_of":"2026-08-15T10:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7d3070d48fcc43c67e7f40acc4d5f98e22424546399b6a559907eb88b6e1dd73","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T05:28:54.374342Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/1909.01193/citation-record","integrity":"/paper/1909.01193/integrity","json":"/paper/1909.01193/citation-record.json","paper":"/paper/1909.01193"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:28:55.249599Z","title":"Deep learning for multi-path error removal in ToF sensors","venue":null,"work_id":"87a0de7f-47dc-4841-814e-d3168527622d","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.109368Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:92c2c17188883b7670a235be1a33cd3049c19b38b4495ab63248087949a07393","observation_id":"cf876301-7ad7-4f70-bfb2-852febb8bc01","resolution":{"observed_at":"2026-08-14T05:28:55.254683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.235596Z","title":"Alexiadis, Nikolaos Zioulis, Dimitrios Zarpalas, and Petros Daras","venue":null,"work_id":"37a30162-dc5b-47f3-9f66-24c44f77fad6","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.115229Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:d02c696f926e3d11cf1ea9a7b1976e4b4e10f6595c87258799258056174b21dc","observation_id":"d081fadf-6f19-493d-ba61-0003f0323cb8","resolution":{"observed_at":"2026-08-14T05:28:55.240247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.219934Z","title":"Barron and Jitendra Malik","venue":null,"work_id":"0a99ccf8-a39a-4c7a-b7fb-01f20c6eb800","year":2013},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.120928Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:8e8da6b5d87f2afe331d14b161786bdf9b4022a249b3653668530bbc437e7c4b","observation_id":"2020408c-3ca1-4f37-92b2-0e2ec0230106","resolution":{"observed_at":"2026-08-14T05:28:55.224454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.205194Z","title":"Ro- bust intrinsic and extrinsic calibration of RGB-D cameras","venue":null,"work_id":"90143b3c-9159-4f88-a815-46a16d6df988","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.125923Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:a925580b539f516939a63f06e8c9f90bab1dbcea1a70d77c485f61419f8e3d58","observation_id":"a8e6c1f2-e766-4932-8845-b02746c8f938","resolution":{"observed_at":"2026-08-14T05:28:55.210000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.189648Z","title":"Noise2Self: Blind denoising by self-supervision","venue":null,"work_id":"e2edc44d-f2e3-4c2e-8ce1-77b05969b87e","year":2019},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.131304Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:3540d26f832f086772a793c97577a3e6306477a293119eb56cb5d2bd762ce376","observation_id":"1adfbdb7-d592-435b-9e33-284cfcee181f","resolution":{"observed_at":"2026-08-14T05:28:55.194843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.174924Z","title":"Robust optimization for deep regression","venue":null,"work_id":"49b3db59-b5f1-4922-9310-18ceb753008a","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.136304Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:985c18d227656baa5c3b3564f6eb35dbf7bbfa02e79f795aae17720dc340b295","observation_id":"985eb944-b8e7-4ba6-9bdb-2ac496b742aa","resolution":{"observed_at":"2026-08-14T05:28:55.180005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.159261Z","title":"Fast MRF optimization with application to depth reconstruction","venue":null,"work_id":"8b45849c-40ea-4414-85fa-e651217a78e6","year":2014},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.141790Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:77c04b2323386b722b69115072c94351f03e30be0eeb0e2e3bea607420b086b8","observation_id":"d4c75a88-3bfe-4236-8e3a-d47344371357","resolution":{"observed_at":"2026-08-14T05:28:55.164305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.144629Z","title":"LiDAR-Video driving dataset: Learning driving policies effectively","venue":null,"work_id":"38726f65-b10e-435d-9fb1-b7a6d10e57db","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.146562Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:c8c73c1efd5da31caeea3a35d95109da5fd9f49f2487ff156c61158c19109d19","observation_id":"063a105c-ae5a-4ea2-8a82-af3e1f7954f6","resolution":{"observed_at":"2026-08-14T05:28:55.149309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.129204Z","title":"Fast and accurate deep network learning by Exponential Linear Units (ELUs)","venue":null,"work_id":"952cc36e-7127-4153-8472-d9aa7fd5e4fb","year":2016},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.151617Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:fb420220bb884c25c22a9c2ae703aa14425f7ed524f5581ba0f31c1f3872b7ce","observation_id":"5a76b510-3a80-4350-9e29-85e75763cccd","resolution":{"observed_at":"2026-08-14T05:28:55.134585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.112961Z","title":"BundleFusion","venue":null,"work_id":"bde80fb3-60ac-46e3-ba22-44f40b0eb567","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.156644Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:9e0e0e5222dc79432b31c8c73a31f2e7ce4d36a71069af95215f814933fc4926","observation_id":"cdab1640-4d4b-46ad-ad63-624d0e826f2a","resolution":{"observed_at":"2026-08-14T05:28:55.118657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.098718Z","title":"Understanding the dif- ﬁculty of training deep feedforward neural networks","venue":null,"work_id":"f2375948-4b26-4223-bd17-77e89f42c80e","year":2010},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.161673Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:e438b78a1307aabe2253f8fcab7a5093fc914b25792804a1d9e5509e48b670b8","observation_id":"b1a92937-bd48-466b-9742-b10ecfd595ef","resolution":{"observed_at":"2026-08-14T05:28:55.103246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.084077Z","title":"Learning dynamic guidance for depth image enhancement","venue":null,"work_id":"116dab5c-0466-4c87-b5c3-e96c40973b8e","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.166394Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:369d5a9b0e8886573cf187ca6db7994cdef32d08f21b1a1825d567ea7f247240","observation_id":"395b9b1c-babd-4196-8a1d-cce193353b6e","resolution":{"observed_at":"2026-08-14T05:28:55.089547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.069294Z","title":"Real-time geometry, albedo, and motion re- construction using a single RGB-D camera","venue":null,"work_id":"7b9c68f1-a909-4fea-8764-ea426436b843","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.171065Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:b00402b32e0ad079eb3d32ed3fdb65044e4d71c5b9d7ea459589d48e8858db6a","observation_id":"d2f6a0cc-a2d0-4ba9-a63f-af52e1ea9720","resolution":{"observed_at":"2026-08-14T05:28:55.074141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.055024Z","title":"Tackling 3D ToF artifacts through learning and the FLAT dataset","venue":null,"work_id":"0d53529b-1708-4ef6-a6b3-867adb76471f","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.175739Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:0b44ad0156da6031fe035611248cc8527486c36300f8625d51c7918a8ab4b426","observation_id":"3925291d-1cc5-4972-90f7-3004d43a1a9c","resolution":{"observed_at":"2026-08-14T05:28:55.059702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.039482Z","title":"Robust image ﬁltering using joint static and dynamic guidance","venue":null,"work_id":"fe79d94c-e6d5-414a-b708-1029b0db995d","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.180442Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:edc9da5cd506db483ca1974ea0778acdcd54dbf40c8156345af08f9b41bee41f","observation_id":"bc11f384-cc2a-4755-beb6-1574f90f0672","resolution":{"observed_at":"2026-08-14T05:28:55.044039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.024372Z","title":"High qual- ity shape from a single RGB-D image under uncalibrated natural illumination","venue":null,"work_id":"b56ef215-3b3e-4cd4-92f3-ec1afdd13d8f","year":2013},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.185068Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:594375b274851831c5b227b37cb333ee5efdc3669b5b7b04529a6609585514f3","observation_id":"2b276620-9083-46be-b108-f29ee3f1ef89","resolution":{"observed_at":"2026-08-14T05:28:55.029318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:55.005206Z","title":"Identity mappings in deep residual networks","venue":null,"work_id":"94b5a53b-6bdc-4260-bbeb-2369742387f3","year":2016},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.189591Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:4e40ff7b04561d97f4b888c6e81e1b846df97160660a18a8e958c8332c40a29a","observation_id":"428787d7-4862-47cf-be97-ee6f39d13535","resolution":{"observed_at":"2026-08-14T05:28:55.011076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.988357Z","title":"Joint depth and color camera calibration with distortion correc- tion","venue":null,"work_id":"751aaa56-46d1-47e4-b9fd-3c6e5c24c2cc","year":2012},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.194270Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:5ecb7e54ec57c68540a4f9a905e32d4b6607e083e77542ceb7bacb19ff5a1db3","observation_id":"2b856b40-5eb1-4f77-8b28-efd2bae9475a","resolution":{"observed_at":"2026-08-14T05:28:54.992903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.971817Z","title":"Spatial transformer networks","venue":null,"work_id":"fc807cf8-fefc-4089-9360-e804267aa790","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.198954Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:dfe3bcedca7a76963380f30019866d6cf927adda744d43e7aec879e8466c4686","observation_id":"a9908039-2031-4fb8-b257-659749e6ebdb","resolution":{"observed_at":"2026-08-14T05:28:54.977214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.956336Z","title":"Reconstruction-based pair- wise depth dataset for depth image enhancement using CNN","venue":null,"work_id":"8d3ff4b9-ba83-449d-b640-249d17eaa047","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.203677Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:d6d1863d56b6c30db5bd7131b757781a42588c92241cbb58c0966ebe2c556db0","observation_id":"d706ccfd-813c-43f6-86ff-396720573486","resolution":{"observed_at":"2026-08-14T05:28:54.961435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.941799Z","title":"Screened poisson surface reconstruction","venue":null,"work_id":"e6d26e63-8c13-4aa3-9089-6e67fa1b8872","year":2013},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.208181Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:72e697ff3067e896d9e1c491e41c8280982c1a003513878bc99a912ce7a164f2","observation_id":"a24c44b5-6d22-436c-b59c-830329f63abb","resolution":{"observed_at":"2026-08-14T05:28:54.946405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.927732Z","title":"Intel (R) realsense (TM) stereoscopic depth cameras","venue":null,"work_id":"c0998697-f79b-4dbe-915c-3d00bcbcdb7d","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.213068Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:0b1a689468ad0867e8403c3ec0ecc4ec5993ab1233c32f92a6be007dd7c54b12","observation_id":"50ba8106-8dd8-41d9-b54c-b571e09190b5","resolution":{"observed_at":"2026-08-14T05:28:54.932183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.217958Z","title":"Kingma and Jimmy Ba","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.217958Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:6bbc3b8fee5d5da727ee316ddfc343258c207aaa43776534b3fac3f25b8786ad","observation_id":"fabbafbd-4a59-481e-816b-f40e37900e8a","resolution":{"observed_at":"2026-08-14T05:28:54.217958Z","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":"2026-08-14T05:28:54.901601Z","title":"Cohen, Dani Lischinski, and Matt Uyttendaele","venue":null,"work_id":"f1793639-785a-4712-b8c0-93cad77fc458","year":2007},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.223036Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:1b484d69c40d35e675c1360870b051960815b5207c64437861dddf5e559ca856","observation_id":"e2d71dcf-faf4-4090-8e85-b8424a1f2095","resolution":{"observed_at":"2026-08-14T05:28:54.906481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.886117Z","title":"Noise2V oid - Learning denoising from single noisy images","venue":null,"work_id":"b263f72e-d26e-409c-990d-d2175804a062","year":2019},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.227969Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:f272285550d95a63fa52174c6a1cdedcb6888ba73b6a9c16f2f372fc35ce9f0e","observation_id":"a5396d53-f2e3-4cc2-aed0-33389193b3ed","resolution":{"observed_at":"2026-08-14T05:28:54.891106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.869967Z","title":"Data- driven depth map reﬁnement via multi-scale sparse represen- tation","venue":null,"work_id":"13db691f-ffcc-4806-98e6-43ad974420a8","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.232877Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:29a1414111ac6960d10cd5758cd8c2d1daa78a517455030a5b8fb6191cf9808c","observation_id":"03ef7ac3-ca32-4320-8c56-7c5544efbfd8","resolution":{"observed_at":"2026-08-14T05:28:54.875133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.853408Z","title":"Deeper depth prediction with fully convolutional residual networks","venue":null,"work_id":"cdb1fab1-3532-4e47-bff7-022c47ba4904","year":2016},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.237587Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:e8ddb5f0f9ad4f2b81a14863f03bc655b0e975301b29074bd05221a1e0151e05","observation_id":"4de16d44-8f77-486e-b7de-60110de80e0d","resolution":{"observed_at":"2026-08-14T05:28:54.858221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.838317Z","title":"The adaptive BerHu penalty in robust regression","venue":null,"work_id":"065040f4-a295-4fbb-9ea5-106c3f6bac40","year":2016},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.242289Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:e3c0b8fd32d1f3d8464da62a0e6aee41cf9ee74e46109cd972d43ae942699fae","observation_id":"06d28247-6fcd-4952-8573-1747b5d07b06","resolution":{"observed_at":"2026-08-14T05:28:54.843273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.823187Z","title":"InteriorNet: Mega-scale multi- sensor photo-realistic indoor scenes dataset","venue":null,"work_id":"a6756a9d-8087-412a-be21-578f3a637df9","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.247012Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:c44dba4efcca049ebcbbe734ef93df9c0cd83c2341fc378a8657f2c8f492ae59","observation_id":"f9ed853f-1756-44f6-9e5b-be1f875b6cc1","resolution":{"observed_at":"2026-08-14T05:28:54.828320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.808610Z","title":"Joint image ﬁltering with deep convolutional net- works","venue":null,"work_id":"62a779b4-23c7-4746-8650-74f7e93815e8","year":2019},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.251774Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:4b5fcc4d03d65b8752486bc9d6bf6d60ea9d3b938d6b9933b45c8bf69d6896fb","observation_id":"2ed4d9e4-190e-4580-973e-ec20c45abf5f","resolution":{"observed_at":"2026-08-14T05:28:54.813307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.793185Z","title":"Reda, Kevin J","venue":null,"work_id":"30577e8a-fbd7-4b7a-89f0-688fe4b089c4","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.256634Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:8ffaa0c4294eda8ce7dc5d973c3b6095c4f2503f7dbf4147c485a592c1659db4","observation_id":"1650fad4-8257-4937-b803-562a8e516b4d","resolution":{"observed_at":"2026-08-14T05:28:54.797780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.261539Z","title":"Depth enhancement via low-rank matrix completion","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.261539Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:ecbb3a210ab37107cf13c013f92c8c167934ecfffe7383514744dfe255ad3ae7","observation_id":"1988790b-806c-48d9-826a-97567e47c9a5","resolution":{"observed_at":"2026-08-14T05:28:54.261539Z","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":"2026-08-14T05:28:54.766142Z","title":"Kim, Xin Tong, and Diego Gutierrez","venue":null,"work_id":"4f16e9ef-a672-4175-9f97-9032977b6b83","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.266235Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:909299c08f496d53717349b85bcb48ffc205a5ddf0d61a7227bfa267cd51c928","observation_id":"8458630d-8346-404f-9a58-b57a40edbc80","resolution":{"observed_at":"2026-08-14T05:28:54.772077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.749609Z","title":"Plane ﬁtting and depth variance based upsampling for noisy depth map from 3D-ToF cameras in real-time","venue":null,"work_id":"33d62149-9f19-4cdf-a55d-8e1c2ae89187","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.270973Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:4ee8bf653d756e807e9c2de94c3c31862ce3df2d60b5c0b6fcc840e3c5c182ed","observation_id":"a20a57e1-e8b2-4fa8-8f0f-3e16c3a96543","resolution":{"observed_at":"2026-08-14T05:28:54.754604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.734760Z","title":"Dictionary learning from incomplete data for efﬁcient image restoration","venue":null,"work_id":"ce3193f0-2924-4c9a-9778-0753fe3c8b81","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.275497Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:25300a10d52717a83f901c43bbacae3f49a5b2d2b30f427b30b5bfbb6809a780","observation_id":"72b8eb7b-b0ae-4128-b3eb-5f762dbbff97","resolution":{"observed_at":"2026-08-14T05:28:54.739564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.719955Z","title":"Newcombe, Shahram Izadi, Otmar Hilliges, David Molyneaux, David Kim, Andrew J","venue":null,"work_id":"ba443796-7f5e-43ba-a616-377a9c651f18","year":2011},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.280172Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:966b824fe890054a9a9b2c347e15083130c902613e756417d1f7957b9a975b4d","observation_id":"1477bd47-88bc-4663-9785-c8f09bbc60c5","resolution":{"observed_at":"2026-08-14T05:28:54.725030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.704548Z","title":"Bruckstein","venue":null,"work_id":"9523a862-28cb-441e-81b6-f189afad69e6","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.284975Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:cb880d9530fe9c89160952afebac79fddeaa08b4975faf4462e633198d79e43c","observation_id":"97fcfc1a-754e-469f-b8d8-e17d384256cc","resolution":{"observed_at":"2026-08-14T05:28:54.709697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.681674Z","title":"Markerless structure-based multi-sensor calibration for free viewpoint video capture","venue":null,"work_id":"1d9148f8-26dd-4d30-9fc9-0d597733452b","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.289758Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:f6832c1977962fe15662cd4cf66f027faeee7263a268eef91d657d6d9bc7fc10","observation_id":"e8359fec-0192-4eba-854b-8f7682f34fe3","resolution":{"observed_at":"2026-08-14T05:28:54.689722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.294495Z","title":"Automatic differentiation in PyTorch","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.294495Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:eb6939370eb476f58eb954bc6b90d6789f7892499ea526a32cc67c83013d4a5e","observation_id":"9cd65cde-dce2-485a-b970-a4e94a59f1f7","resolution":{"observed_at":"2026-08-14T05:28:54.294495Z","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":"2026-08-14T05:28:54.653766Z","title":"U- Net: Convolutional networks for biomedical image segmen- tation","venue":null,"work_id":"e19403da-059b-4bbc-824d-2d78115ca947","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.299591Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:5c72797be39839a534c257c65e96d2e8e125e8f8c9c0ab7550e9de094e3ba710","observation_id":"27c44578-1af8-42af-8697-95edf6b937d9","resolution":{"observed_at":"2026-08-14T05:28:54.659175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.636531Z","title":"The xbox one system on a chip and Kinect sensor","venue":null,"work_id":"d838abc2-e268-49c1-baf7-de2b06f4e2c8","year":2014},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.304605Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:6cac5f45e21018429e2da95c551b3d93bf523fda4077dea565b32ab1dafb08c3","observation_id":"96559a6a-1c7f-4322-b217-85b23934d784","resolution":{"observed_at":"2026-08-14T05:28:54.643032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.619901Z","title":null,"venue":null,"work_id":"7ff31e96-7789-4492-b78b-29073d5a1ec7","year":2013},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.311205Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:149bc53a466bf272a49a6975f04a98b5cf1e1b96518e9fcd2c256e3f31da8bdb","observation_id":"cfebaeaa-1d88-40dd-8146-e384f7c0ba53","resolution":{"observed_at":"2026-08-14T05:28:54.625128Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.603684Z","title":"Mutual- structure for joint ﬁltering","venue":null,"work_id":"73377ebb-47f4-4dae-8e5e-338111c55ce6","year":2015},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.316455Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:7b723280ade1e646db20cb80ca5ea763ba2dcabc6c3407c4a895622c7881482a","observation_id":"e4ffddd2-b57d-4b43-b0ad-348357f93a16","resolution":{"observed_at":"2026-08-14T05:28:54.608716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.586388Z","title":"A low-cost, ﬂexible and portable volumetric capturing system","venue":null,"work_id":"9587068c-3bdf-429d-aa09-ee8a78eee549","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.321813Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:73470cd5cbc8fb6915be213b75ae429f5285ddb8c7c231671f99b3d26c802dd7","observation_id":"46a99b37-e791-4cba-9db7-0f4ac22e57e0","resolution":{"observed_at":"2026-08-14T05:28:54.591778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.569715Z","title":null,"venue":null,"work_id":"70455cd0-88d3-41d8-97fe-2cf741034735","year":2010},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.327003Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:2a8e97a96f63c46a25698f0cdccf5e537d489be006007c8f5e8ef7628ce208b4","observation_id":"af1f5533-ae07-405f-a0de-153595758f4d","resolution":{"observed_at":"2026-08-14T05:28:54.575559Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.554072Z","title":"A precision analysis of camera distortion models","venue":null,"work_id":"31012c4f-e9f5-4e93-94cc-d73f71add6b7","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.331830Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:75623fb7f571ebc072ea948be9917515d082c20189b278c288cbff96427507ab","observation_id":"20359cba-ff70-4085-9612-5129af1cd719","resolution":{"observed_at":"2026-08-14T05:28:54.559136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.537907Z","title":"CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction","venue":null,"work_id":"4ca3d99d-d3aa-4a02-b54d-72bf2d5c55d8","year":2017},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.336686Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:b281ab644b6718f8ba72ba204c7afd497de3ca56380e756aa15576983c4b25d5","observation_id":"95109727-3229-4ac6-be6a-82a19a7ecac7","resolution":{"observed_at":"2026-08-14T05:28:54.543003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.341691Z","title":"Bilateral ﬁltering for gray and color images","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.341691Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:2420643fa6df007204836828d1d5fbfcd040505a3c1b3e49c275a3687f0ccacc","observation_id":"84d43a2b-e1a5-4dd9-be37-4d323228237a","resolution":{"observed_at":"2026-08-14T05:28:54.341691Z","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":"2026-08-14T05:28:54.506915Z","title":"Layer-structured 3D scene inference via view synthesis","venue":null,"work_id":"25615688-54cc-47f1-82d9-95b6840667f8","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.346877Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:db77fc6a41c4719d5e7df80f450d78480dec7be9a210bdc9fd9507e1c6cc2d2a","observation_id":"570abb7f-d3ec-4163-b0c3-26b6db153e98","resolution":{"observed_at":"2026-08-14T05:28:54.513346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.485212Z","title":"Real- time shading-based reﬁnement for consumer depth cameras","venue":null,"work_id":"20af9f34-5e6c-4c3c-8105-dfb6378669fb","year":2014},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.352798Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:e2ac87240f2f72e32dda0456ef593cf8c133b924b8d8a5215b60b32246ee1eb0","observation_id":"4f977ff9-8bc3-4d63-a8dc-fd7efdaec664","resolution":{"observed_at":"2026-08-14T05:28:54.490731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.465203Z","title":"DDRNet: Depth map denoising and reﬁnement for consumer depth cameras using cascaded CNNs","venue":null,"work_id":"f330bbc3-5560-4104-ac69-591cd2ca7f0a","year":2018},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.358439Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:d7a0fb496522fc22370c63ae3de5ac99dd6af044e8031f7b25a39f19adb26849","observation_id":"e425562b-fddf-48ce-af51-5a761ca9e098","resolution":{"observed_at":"2026-08-14T05:28:54.470344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.448225Z","title":"Shading-based shape reﬁnement of RGB-D images","venue":null,"work_id":"700d15f1-de62-4adc-8e8e-fb1967ff85e7","year":2013},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.363256Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:e0f0f792a2cf7affa9bffbbdf1fe672b2f45bcf0547e5a3b1cc3473588dbe69b","observation_id":"d9052ff3-8334-482a-9ac3-0a97e60cf1c2","resolution":{"observed_at":"2026-08-14T05:28:54.454195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.431776Z","title":"Rolling guidance ﬁlter","venue":null,"work_id":"dbe7f039-9ea6-4462-b232-df08f74c68ba","year":2014},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.368973Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:a8261b8ea85f5d1cc660b740c144363e6de10818727499c63688610ad69629a3","observation_id":"2d9f3273-2375-41bf-b5b6-4f1a082eb216","resolution":{"observed_at":"2026-08-14T05:28:54.437081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T05:28:54.413274Z","title":"spraying","venue":null,"work_id":"f5a375b0-5f54-48d6-b994-b3b308dd6158","year":2000},"citing_paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T05:28:54.374342Z"},"links":{"citing_paper":"/paper/1909.01193"},"observation_digest":"sha256:13eb2ee02637f7ecdcc6dbd921380d64a8f1b3c01e40b8a4c8e02501595cea6a","observation_id":"e3936770-c3d7-4f2a-bedb-3d291f383952","resolution":{"observed_at":"2026-08-14T05:28:54.419524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1909.01193","last_updated":"2019-09-04T09:18:14Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T08:20:21.343414Z","submitted_at":"2019-09-03T14:08:32Z","title":"Self-Supervised Deep Depth Denoising"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":48},"total_outbound_references":54},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:1909.01193."}