{"as_of":"2026-08-08T17:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de1521752b1c605ac59f26488c6664c3d9d6e8bf5a8b2b5ccfcabce970a77449","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T23:33:16.443338Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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":"2026-08-07T05:18:57.561946Z","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":"2026-07-02T02:36:27.314659Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.08836","snapshot_observed_at":"2026-08-07T05:18:57.561946Z","title":"Survey on single-image reflection removal using deep learning techniques,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.561946Z"},"links":{"cited_paper":"/paper/2502.08836","citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:f021016db2d94e85f239de44892db187261c87c4a3894574aac494f89529ce45","observation_id":"90a3d25d-c8f3-45ea-bcb9-4a66c7e3fb13","resolution":{"observed_at":"2026-08-07T05:18:57.561946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"cited_work":{"arxiv_id":"2502.08836","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.08836","snapshot_observed_at":"2026-07-02T02:36:27.314659Z","title":"Survey on single-image reflection removal using deep learning tech- niques.arXiv preprint arXiv:2502.08836, 2025","venue":null,"work_id":"8bc459f4-7008-4914-963c-7f4dcf404778","year":2025},"citing_paper":{"arxiv_id":"2606.04107","last_updated":"2026-06-02T18:11:20Z","snapshot_observed_at":"2026-07-06T23:44:14.261541Z","submitted_at":"2026-06-02T18:11:20Z","title":"Reflection Separation from a Single Image via Joint Latent Diffusion","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-06-28T10:47:22.111357Z"},"links":{"cited_paper":"/paper/2502.08836","citing_paper":"/paper/2606.04107"},"observation_digest":"sha256:9d455e79fd282d5ee245c1fc1d75c5f492c2def4a47362347b53e18274ea24fe","observation_id":"f1dfb44f-9fe8-4190-a375-65e35b8f3070","resolution":{"observed_at":"2026-07-02T02:36:27.316183Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.08836/citation-record","integrity":"/paper/2502.08836/integrity","json":"/paper/2502.08836/citation-record.json","paper":"/paper/2502.08836"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.437784Z","title":"Over the years, various techniques have been proposed to solve the SIRR problem","venue":null,"work_id":"bf0611b5-7236-4074-a5c6-516cb18c8852","year":2015},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.242320Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:ba08adcab7ff565c5bb785d1a9d6f45437de5355fdc0a9161a71ea0c072ed961","observation_id":"bcabfca6-f4b3-4eac-a9c4-27d4246a32d2","resolution":{"observed_at":"2026-08-07T23:33:17.442519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.417617Z","title":"single image reflection removal","venue":null,"work_id":"203f5eb1-83a7-43d2-af05-88f3aab253ab","year":2017},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.247876Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:b574b9baf4f4d2eb7f0e2c37210625e4f93cab3ebd2b5bd76170f915f5f6891d","observation_id":"d0db59f0-072c-4749-9b0d-4d075f692ec7","resolution":{"observed_at":"2026-08-07T23:33:17.427219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.341514Z","title":"To this end, researchers have proposed various hy- potheses","venue":null,"work_id":"d07e18ea-1b89-4297-8b80-314bad284ac2","year":null},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.252570Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:5eba4b2af0363d8737458a5dd608e2c1c2e3489c809b40434af789157a1205ee","observation_id":"5b19b1ff-c926-457f-91c0-f126dbda5bb5","resolution":{"observed_at":"2026-08-07T23:33:17.387887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.290744Z","title":"The learning objective is introduced i n Section 4.4, with a comparative analysis of models in Table 1","venue":null,"work_id":"a777cdca-3878-401c-9773-e2506442e893","year":2018},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.257001Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:0cdc3795268e43a3bc955f63189d7d2e36a0fdab8fb8b53b16bf0ffc75155ffd","observation_id":"0495d5ad-9802-4bf7-90b1-86c994e48b76","resolution":{"observed_at":"2026-08-07T23:33:17.314142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.266374Z","title":"Data Acquisition The datasets for SIRR are a critical aspect of developing effective deep learning models","venue":null,"work_id":"62e038dd-111a-4254-888a-62d4fb1492fe","year":2017},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.262682Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:dcb01456b95045c4dfcae47ee5581f621e7ee5c140a9db15889824fbb4da99de","observation_id":"bfa3edbc-be4a-4efe-b707-5513e6500a78","resolution":{"observed_at":"2026-08-07T23:33:17.271244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.251065Z","title":null,"venue":null,"work_id":"dbf6b2d4-4ba6-4f04-b688-45a5671221d8","year":null},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.268079Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:9163b269adb4f259b0f69340ab5d4df5cdf09216b3617b96e3c8733065f118bc","observation_id":"734a52ca-074f-49e7-8e72-61a8ce2e0e1b","resolution":{"observed_at":"2026-08-07T23:33:17.255964Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.236368Z","title":"We first describe the methodology used for our bibliographic search","venue":null,"work_id":"7cf3a98b-a26e-4f4b-bdad-793a175c68ad","year":null},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.273207Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:0d5f84cd9b7736c0f5e617e7a7eaf0a4c6f2837a1d4e8d2b5d5c6f5006230945","observation_id":"1a1f3c91-9b1d-4052-8782-cc8e38f095fc","resolution":{"observed_at":"2026-08-07T23:33:17.241301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.221526Z","title":"Separating reflections from a single image using local features,","venue":null,"work_id":"08c727b8-0287-4fb5-b5c0-c0fbda876b76","year":2004},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.278299Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:68ed2c5318c68e8e8c5cf2f3f3b1a3981eabfa6d3f277caec8b9daba6ccc27d7","observation_id":"c41a7739-b7c8-4360-9ced-395695638fbe","resolution":{"observed_at":"2026-08-07T23:33:17.226324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.181287Z","title":"Learning to perceive tr ansparency from the statistics of natural scenes,","venue":null,"work_id":"5eb93a5d-578d-421b-a931-92639867a14b","year":2002},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.283123Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:1a5801d26fc79fe86131ae017372a5dea312591f9827670d4930da0c5e19311b","observation_id":"213e7209-0899-4c99-8daf-3644d215ef3c","resolution":{"observed_at":"2026-08-07T23:33:17.195322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.164989Z","title":"User assisted separation of reflec tions from a single image using a sparsity prior,","venue":null,"work_id":"db7d79d4-898b-4f60-a02b-d52faa42e229","year":2007},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.288425Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:e1b2800781b3881d4d643e504d89dda202ad0646c30c41518d74101a1dfad9f1","observation_id":"959c6325-5443-4c24-9966-93f19a2e7547","resolution":{"observed_at":"2026-08-07T23:33:17.170054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.148996Z","title":"Single image layer separation usin g relative smoothness,","venue":null,"work_id":"625039ce-194a-49ed-ac20-f98ea8d795c7","year":2014},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.293419Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:4cafb1d3165bfa3fc0972a5c5fc84f2e6eef88769aad514d79fc77e8a3b53709","observation_id":"5a030c74-5667-469d-8b6e-072a88fcd873","resolution":{"observed_at":"2026-08-07T23:33:17.154328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.129818Z","title":"Fast single i m- age reflection suppression via convex optimization,","venue":null,"work_id":"62d23dad-31e5-4582-9e27-71414a8b102a","year":2019},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.298374Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:a08cc660cd2686db3e3d60ca0f3704ab96bb17768b110443289c330138140f6a","observation_id":"c50a3dd8-f81f-4135-aab4-038e7b8c9f6c","resolution":{"observed_at":"2026-08-07T23:33:17.134983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.113493Z","title":"Depth of field guid ed reflection removal,","venue":null,"work_id":"580488b2-3ac4-480e-bf67-3d5da28572dd","year":2016},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.303259Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:fdce2742a38aaf5750e7114dabee1b76ee512d6c95d2578a64197df0a56bca7f","observation_id":"b16300e7-bd82-49b3-81a9-4ab5dec21729","resolution":{"observed_at":"2026-08-07T23:33:17.118582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.097449Z","title":"Reflec tion re- moval using ghosting cues,","venue":null,"work_id":"db273862-e0a8-43fc-9b95-60a74cda7288","year":2015},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.308496Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:6271971c2d2bd522499d157d6685d5a14f1878859fbebf815c85bf41727f4e28","observation_id":"7b953698-193e-4f25-b9bb-3e56e97117f3","resolution":{"observed_at":"2026-08-07T23:33:17.103076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.080893Z","title":"Robust single image reflection removal against adversaria l attacks,","venue":null,"work_id":"0159f2e9-b823-43a7-9c8f-5f1e42918ce6","year":2023},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.313345Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:19b31d82e099f1f3c82d7463bd5bf29b468180c6aabc5389d5e80750266f0535","observation_id":"40d1060b-2875-458f-b2f2-818f54c2a0ad","resolution":{"observed_at":"2026-08-07T23:33:17.085885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.064841Z","title":"Single image reflec- tion removal exploiting misaligned training data and netwo rk enhance- ments,","venue":null,"work_id":"503df243-6e32-4c67-ab4f-6dd5f1f6a197","year":2019},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.318080Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:ad6514fffc130366267165993d41fef2e4c5ccda77ea444ace52225649230f22","observation_id":"b2780683-881b-4fa5-a8e2-d8d278261e88","resolution":{"observed_at":"2026-08-07T23:33:17.069893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:17.019593Z","title":"Benchm ark- ing single-image reflection removal algorithms,","venue":null,"work_id":"fa59a924-82b4-4d45-9fb7-64ccaaf1a0f4","year":2017},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.322886Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:894e9c2c10191bbce23dfcfdafe28ce235503775986a4ef5c1319586d6a8b886","observation_id":"9f93129b-bc3c-446b-b8a9-cb31b31803e3","resolution":{"observed_at":"2026-08-07T23:33:17.040683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.966133Z","title":"Be nch- marking single-image reflection removal algorithms,","venue":null,"work_id":"fed7fb7d-26c4-4dd6-9a3c-626cfa492861","year":2022},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.327891Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:39590666ca75c1be4bed3647fa578b5fcc6b047849fd49f658d1703adf344dd2","observation_id":"9dc64224-7339-4d6a-9326-97a7960edd06","resolution":{"observed_at":"2026-08-07T23:33:16.990230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.904982Z","title":"Single-image reflection removal using deep lear ning: a systematic review,","venue":null,"work_id":"c39dab08-b0d9-487b-aa19-5a38050f9b97","year":2022},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.333060Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:5a536fa128bb6b276025413c07621c95194e720f19d640f6d5e10a8f3efd7c8a","observation_id":"ed10ea88-80a1-41c0-8de8-8876733323bb","resolution":{"observed_at":"2026-08-07T23:33:16.931487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.838178Z","title":"A generic de ep archi- tecture for single image reflection removal and image smooth ing,","venue":null,"work_id":"c0f9bfe9-e523-49ba-93b6-558f3d93ae88","year":2017},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.337586Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:d03eb39cc4eed061147d48945dc3bddf3ab815f5ba1cbad46f158108648ebfae","observation_id":"0ba29870-beaf-4276-bb4e-94929b7af2ea","resolution":{"observed_at":"2026-08-07T23:33:16.867675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.821370Z","title":"Single image reflection sep aration with perceptual losses,","venue":null,"work_id":"4845a328-6fa2-49da-89fb-8cba343cdd13","year":2018},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.342799Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:ab408ce2fb246546b5b18f21b66ba4be7410f1742935816d5976a8adca540551","observation_id":"da2a9607-6ee1-469e-9de9-b41cd4d0b631","resolution":{"observed_at":"2026-08-07T23:33:16.826582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.806459Z","title":"Trash or treasure? an interactive dual -stream strategy for single image reflection separation,","venue":null,"work_id":"7928ff8c-bb1f-4290-9e2f-5ab4174b17d3","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.347613Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:3430a43e0d99cc45a29f80f59856041bb4d13a17b31d5345404f08d25f835428","observation_id":"9dda03a5-09cd-4b13-8f5f-087d20263502","resolution":{"observed_at":"2026-08-07T23:33:16.811126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.791567Z","title":"Single image reflection separation via component synergy,","venue":null,"work_id":"30526245-d2e4-411d-8655-1d5d3da25305","year":2023},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.352330Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:ea10e9f2a1ace8a17cde6865f51cf7aa41d1f6490aa67377ebccc099da7a9762","observation_id":"87eba507-573f-4653-8c15-def7d63cc415","resolution":{"observed_at":"2026-08-07T23:33:16.796386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.776959Z","title":"Reflection scene separation from a single image,","venue":null,"work_id":"54e1bc94-15df-4463-9ef2-569ab2c95a2c","year":2020},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.356968Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:531832e195b8fc5a1b191b7225aec04ca8223f848dc1645419eef001d5fec16b","observation_id":"faed0d9e-40cf-4794-94db-e7a74c3a9be7","resolution":{"observed_at":"2026-08-07T23:33:16.781605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.761774Z","title":"Two-stage s ingle image reflection removal with reflection-aware guidance,","venue":null,"work_id":"63ca2f03-8c8d-49c5-b71c-c6ec5d23edcb","year":2023},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.361507Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:9ba301987f388107aa2b813dd435405a1ac80f3f9313f1b717705923a0bdd713","observation_id":"3b461e70-15d1-4734-8543-60abe0cd8040","resolution":{"observed_at":"2026-08-07T23:33:16.766954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.746968Z","title":"Crrn: M ulti- scale guided concurrent reflection removal network,","venue":null,"work_id":"7d6e4af4-ec36-4052-a32c-26ee6b4a20b5","year":2018},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.365711Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:241af6b76b5475e70d0e4428b43c6427906cec2afe80e9c4b65e7470ba5ad866","observation_id":"3e8de497-c5db-48b0-bfa4-5a2ed573b3c9","resolution":{"observed_at":"2026-08-07T23:33:16.751977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.731912Z","title":"Seeing deeply and bi direction- ally: A deep learning approach for single image reflection re moval,","venue":null,"work_id":"9ec89466-8427-4062-9eca-9cfa846a1d26","year":2018},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.369756Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:7afec2dc1d37e5db3f12202077932fa0c4eeb26527311ab58b724b17f627d402","observation_id":"896c63d8-15cc-420c-97fe-30a0df1bd12f","resolution":{"observed_at":"2026-08-07T23:33:16.736527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.716424Z","title":"Single i mage reflection removal through cascaded refinement,","venue":null,"work_id":"256603bb-7e0a-47ce-98b8-26a93213936a","year":2020},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.374743Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:700f7f8642d12dac0587c8846b1da9c3bb84db798582fa9fbf52e65d2e65f603","observation_id":"3d39e4d5-65b3-4069-8134-44f819f6d3ad","resolution":{"observed_at":"2026-08-07T23:33:16.721424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.701684Z","title":"Single im age reflection removal beyond linearity,","venue":null,"work_id":"4be4cb78-6e9a-4734-b675-a6dbfdc83ddc","year":2019},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.379385Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:3df03e3516020d8e5952d4208897cc65c2c8ff8d8ec3d03eabb2889941212013","observation_id":"13a25da3-45cb-4f4a-90b6-93b1d3abc528","resolution":{"observed_at":"2026-08-07T23:33:16.706574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.687605Z","title":"Locat ion- aware single image reflection removal,","venue":null,"work_id":"0d1ff199-9ee7-4de4-a260-aed99d1bf445","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.383635Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:90cba2d4a590e3b43e07664d54f1f8c55cece017d64685d2bd081075778a0869","observation_id":"73b9508f-05b9-4949-8d5e-9923baa7d69e","resolution":{"observed_at":"2026-08-07T23:33:16.691991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.672310Z","title":"Single image reflection removal with absorption effect,","venue":null,"work_id":"8c59af21-7ec4-4db6-90b1-39ae12705fda","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.387910Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:6a469d9ada43b5ccefb262d8a3a2e92149c29227b773f2509478f42d56d210a9","observation_id":"df47996f-ab0e-4735-94e2-945f83408efc","resolution":{"observed_at":"2026-08-07T23:33:16.677057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.657063Z","title":"Co rrn: Cooperative reflection removal network,","venue":null,"work_id":"8de4d81f-128f-4082-a7d2-08aa6f0f9038","year":2019},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.392196Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:23c3a6f9b2c6133249b42b4d136eb96566b3aae014a34c3a5fb609aa10e01d23","observation_id":"d7784a09-a980-44c0-b4d9-43503127bedd","resolution":{"observed_at":"2026-08-07T23:33:16.662072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.640750Z","title":"Deep -masking generative network: A unified framework for background rest oration from superimposed images,","venue":null,"work_id":"2bea8fa4-5368-49ac-a197-2e7a19c725cb","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.396968Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:a3c1085cb6e5e04f51e5d5e24b3633b59b9ec0009155d9f0cc8dd9bc008cce2a","observation_id":"68619fa6-22c6-4ab4-b65c-8b758bafc10a","resolution":{"observed_at":"2026-08-07T23:33:16.646020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.625169Z","title":"Single image reflection re moval with physically-based training images,","venue":null,"work_id":"8a4b17ac-964f-45fa-b628-4f2bab953def","year":2020},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.401408Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:13ad58bf578c287bb003bcba3c0066c7e39c8a08992e745769f55c594a727454","observation_id":"ad65e00e-8d3f-4a5b-98fe-99b1e8e7ba2f","resolution":{"observed_at":"2026-08-07T23:33:16.630157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.608121Z","title":"Revisiting single image reflection removal in the wil d,","venue":null,"work_id":"e2300ad0-3103-4d14-aa1f-59fdc408bddd","year":2024},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.406001Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:c982e25ce99fa239c655f61f96ca98e39fdd2a6b20042265f020a260c763055e","observation_id":"1170ac48-7ade-42f9-b26e-f86146781d3d","resolution":{"observed_at":"2026-08-07T23:33:16.613620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.592310Z","title":"Languag e-guided image reflection separation,","venue":null,"work_id":"e40fe186-b63e-47a7-8abc-e0437d3aa069","year":2024},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.410760Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:181d6ca047a6f7fa613a7e63382fcd740d58ba4edac6e98bebcb892f83c41ac5","observation_id":"23184ddf-f72f-4cc7-8145-f3c0ed81bbc5","resolution":{"observed_at":"2026-08-07T23:33:16.597264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.576131Z","title":"Single i mage re- flection removal with edge guidance, reflection classifier, a nd recurrent decomposition,","venue":null,"work_id":"2d97b1d3-8925-4de7-b5c6-8807aafad2e6","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.415369Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:d4e4bfef3663e3ee726ce79d2f78a561b6341943e383ed0c4cd3676eea32bf03","observation_id":"11c90b41-ecf0-41ce-9569-22d0572d177e","resolution":{"observed_at":"2026-08-07T23:33:16.581332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.559260Z","title":"V -desirr: V ery fast deep embedded single image reflection removal,","venue":null,"work_id":"9cc0b5e7-1936-4226-b435-ca706ac1c74e","year":2021},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.419753Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:6fe504364123c12f20b6ca1a555341c2270712131424647dde09841b5a485635","observation_id":"5a68115d-99e9-41cb-bda3-e1d45141cf5f","resolution":{"observed_at":"2026-08-07T23:33:16.564763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.542051Z","title":"Perceptual losse s for real-time style transfer and super-resolution,","venue":null,"work_id":"100d4a38-e9c7-456a-940f-0123f36fc61b","year":2016},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.424385Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:4186d620fba805d7909b9e5d5706b4dc948c692503e04139a86dea87f1ace7db","observation_id":"8d722999-7c66-437c-b1a7-03dd54140456","resolution":{"observed_at":"2026-08-07T23:33:16.546993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.526564Z","title":"Generative adversar ial nets,","venue":null,"work_id":"c3afbf76-0393-4617-82eb-f4126d92f312","year":2014},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.428776Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:87184a5f5f7478a25834561f32e5832cc18406f50f21c0e4d00aefa20cdee02d","observation_id":"15977f5a-e690-4a1c-86bd-51a912746bba","resolution":{"observed_at":"2026-08-07T23:33:16.531189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.510705Z","title":"A categorized reflection removal dataset with diverse real-w orld scenes,","venue":null,"work_id":"7b84d6cd-d5a2-4eca-9999-5ce989754f4b","year":2022},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.433779Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:4f960e59e68dee5f01b5f93f809167c8ae47386482ecbab0c5e4804670e00830","observation_id":"e5c9baa8-e9ea-44d5-9311-02d661f39da7","resolution":{"observed_at":"2026-08-07T23:33:16.515760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.495190Z","title":"Benchmarking single-image reflection removal algorithms ,","venue":null,"work_id":"2a3a0372-50d1-475e-a56e-04afc253a158","year":2022},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.438601Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:2f262ca1079d128a069fbe8ee5eee6b1a54c531f6497cc9c348f79f477844d0a","observation_id":"57f510b6-4356-4f3d-9ba0-9f15400ff22b","resolution":{"observed_at":"2026-08-07T23:33:16.500347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T23:33:16.477167Z","title":"Backg round scene recovery from an image looking through colored glass,","venue":null,"work_id":"84048120-946f-4bb6-8c17-2fd14665b4e2","year":2022},"citing_paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T23:33:16.443338Z"},"links":{"citing_paper":"/paper/2502.08836"},"observation_digest":"sha256:af23dd4dfca636e97404ec143ddb6b5931bf268adf31842134a5a400dda38dba","observation_id":"39dd09b5-1724-4c0a-81a8-650c0a2d713f","resolution":{"observed_at":"2026-08-07T23:33:16.483955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.08836","last_updated":"2025-02-12T22:57:06Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":42},"total_outbound_references":43},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2502.08836."}