{"as_of":"2026-08-13T06:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8c90beae433743b26d6714a09829aa678504d48699e908e050ef3610c8e37bd8","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T16:59:33.271202Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2411.13042/citation-record","integrity":"/paper/2411.13042/integrity","json":"/paper/2411.13042/citation-record.json","paper":"/paper/2411.13042"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:59:33.670037Z","title":"Spatial and temporal distribution of clouds observed by modis onboard the terra and aqua satellites,","venue":null,"work_id":"86743e90-d6c0-4a61-a2dd-d4d536c131ce","year":2013},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.140631Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:b1ebb6c37e16439f46b897f998576533f3da48adbff99d8c528fdf38b8acf655","observation_id":"3cb8fccd-213c-47a8-8c6a-b12955f26a14","resolution":{"observed_at":"2026-08-12T16:59:33.672706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.662245Z","title":"Simultaneous cloud detection and removal from bitemporal remote sensing images using cascade convolutional neural networks,","venue":null,"work_id":"18a57231-62ad-4a8b-b09f-7461639f53fd","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.143916Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:39791bda5a51b5aaad04503961c3ff59f764330c6387cb13c090cfcb7e77013a","observation_id":"d221ecb6-01c3-4d9b-bbd1-e7e925078223","resolution":{"observed_at":"2026-08-12T16:59:33.665590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.654906Z","title":"Cloud removal in sentinel-2 imagery using a deep residual neural network and sar-optical data fusion,","venue":null,"work_id":"452caf7b-aded-4f89-a524-119641631471","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.147701Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:87ad768a60f96cac8ef9621024e327a7c40f1e538d3ec14a207e4ba29fdd2aee","observation_id":"9aff49b6-b235-4e89-a1ad-7b295e51ac90","resolution":{"observed_at":"2026-08-12T16:59:33.657745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.646421Z","title":"Sen12ms-cr-ts: A remote- sensing data set for multimodal multitemporal cloud removal,","venue":null,"work_id":"fe273e1d-f89e-43f0-b1d5-353b084d7a8c","year":2022},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.151916Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:ad5d9d2271407f9c13df28d3028351a5bd3ea7012b084aaa68b6ae70f17d11fb","observation_id":"7974b9e6-62db-473c-ba2d-f123a51654a5","resolution":{"observed_at":"2026-08-12T16:59:33.650073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.638585Z","title":"Multisensor data fusion for cloud removal in global and all-season sentinel-2 imagery,","venue":null,"work_id":"55e7982f-8ce8-43a7-aeee-6ad346b7ddb3","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.155476Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:7d41bf524b1723f58d7cfde7bffc28960d652bed26828dc959c2bc1210a71add","observation_id":"bab78385-4026-44ea-8c0c-035aa7e30f43","resolution":{"observed_at":"2026-08-12T16:59:33.641489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.158176Z","title":"Image-to-image translation with conditional adversarial networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.158176Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a53d956cae7e1a93b85a1e7fd884aca64b15981c14d91c90f769d8e15ed6667e","observation_id":"fc738726-a48e-4888-9346-22eda97eb540","resolution":{"observed_at":"2026-08-12T16:59:33.158176Z","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":"2026-08-12T16:59:33.626909Z","title":"Filmy cloud removal on satellite imagery with multispectral conditional generative adversarial nets,","venue":null,"work_id":"1c78487f-53e2-4bf9-a7f1-cb621e25862f","year":2017},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.161038Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:3544f1d2914c7e284aee7ac1747b6d252a6d61d102754bdf493b2cfed6f385db","observation_id":"0ea3619a-2e51-4534-a3a5-f7c4d35642f5","resolution":{"observed_at":"2026-08-12T16:59:33.629536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.620281Z","title":"Synthe- sis of multispectral optical images from sar/optical multitemporal data using conditional generative adversarial networks,","venue":null,"work_id":"2f699040-d8dc-4a48-8284-d31728276b57","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.164388Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a6e0b99d450757efccaa1853af458f063b073d38fd2811cb46ca02e3a2872182","observation_id":"fdf5d427-20cb-4016-ada7-31050a224a04","resolution":{"observed_at":"2026-08-12T16:59:33.622846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.06838","last_updated":"2019-12-14T13:03:31Z","snapshot_observed_at":"2026-08-10T12:18:27.321483Z","submitted_at":"2019-12-14T13:03:31Z","title":"Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks","version":1},"cited_work":{"arxiv_id":"1912.06838","doi":null,"metadata_source":"pith","pith_arxiv_id":"1912.06838","snapshot_observed_at":"2026-08-12T16:59:33.319139Z","title":"Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks","venue":"cs.CV","work_id":"0d47fdf6-a9ea-4b16-aec2-4994674dc4e7","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.166883Z"},"links":{"cited_paper":"/paper/1912.06838","citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:5ac91d771b25d890d2dd1ac209f71a699537eed595bd7324e0da1c5b864dcc5d","observation_id":"45865d8c-db88-4c8b-b6c7-3c0336b7d1fc","resolution":{"observed_at":"2026-08-12T16:59:33.322518Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.614824Z","title":"Uncrtaints: Uncertainty quantification for cloud removal in optical satellite time series,","venue":null,"work_id":"4bde739d-a0c8-4b94-ad8e-16226beea353","year":2023},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.169592Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:865943d79010ead6254bc139ff0ad907610269c550e1ea0151c75977b3ab3669","observation_id":"9f8bd1f4-86cc-4baf-8c1d-89f6b0f25668","resolution":{"observed_at":"2026-08-12T16:59:33.616760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.13015","last_updated":"2020-11-14T08:17:05Z","snapshot_observed_at":"2026-08-12T13:25:02.669099Z","submitted_at":"2020-09-28T02:13:23Z","title":"Cloud Removal for Remote Sensing Imagery via Spatial Attention Generative Adversarial Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.13015","snapshot_observed_at":"2026-08-12T16:59:33.172784Z","title":"Cloud removal for remote sensing imagery via spatial attention generative adversarial network,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.172784Z"},"links":{"cited_paper":"/paper/2009.13015","citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:4213cf7bac53e5df0eec363d3d7f6926dd1861769890110f7de60a30d18bfb1d","observation_id":"402f10d9-b2a6-4c67-a018-096017e55a2d","resolution":{"observed_at":"2026-08-12T16:59:33.172784Z","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":"2026-08-12T16:59:33.609486Z","title":"Generative image inpainting with contextual attention,","venue":null,"work_id":"217a57e7-897c-44cd-b2fc-637f63c1086c","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.175525Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:5777b932054cae478c7a1169ea2a0bb95fe0e1e319f4571b830f1041be65a8a7","observation_id":"92339cb6-f4f9-4f5a-a408-e69950d5b5bb","resolution":{"observed_at":"2026-08-12T16:59:33.611334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.00600","last_updated":"2019-01-03T03:43:38Z","snapshot_observed_at":"2026-07-06T07:24:39.425472Z","submitted_at":"2019-01-03T03:43:38Z","title":"A Remote Sensing Image Dataset for Cloud Removal","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.00600","snapshot_observed_at":"2026-08-12T16:59:33.178008Z","title":"A remote sensing image dataset for cloud removal,","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.178008Z"},"links":{"cited_paper":"/paper/1901.00600","citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:e801a33e54f6da71c08a0baefd7bd2299ee7f1b3fac58637978d5baaa4e540b6","observation_id":"c1c5c924-412f-46e4-889d-6943ebbe798e","resolution":{"observed_at":"2026-08-12T16:59:33.178008Z","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":"2026-08-12T16:59:33.603971Z","title":"Kriging interpolation method and its application in retrieval of modis aerosol optical depth,","venue":null,"work_id":"855675d2-34c1-4f8e-b864-db2abecc6d3a","year":2011},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.180823Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a195c6e40de80906b11e60a2bbacdfa3bacd4ec3432524d3fb068764b0d92d79","observation_id":"bcd0b317-a3a4-47c7-b57d-362354ecbcf6","resolution":{"observed_at":"2026-08-12T16:59:33.606097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.598306Z","title":"Remote sensing image reconstruction using tensor ring completion and total variation,","venue":null,"work_id":"11e0e328-3d9b-4b3f-a388-201cb3a769f5","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.182779Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:1fc21da4703e70674d072eb72ded0e6dc027d7bb43341dd6c1a3516a52775149","observation_id":"28405069-14fb-41e0-86be-3d247ad44feb","resolution":{"observed_at":"2026-08-12T16:59:33.600305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.592190Z","title":"Image completion approaches using the statistics of similar patches,","venue":null,"work_id":"c192412c-1470-47e7-921d-d2a4866596bd","year":2014},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.184573Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a1d3c15edafea3e33b9ea43f557e4854a7e6797ce8bc50d11bb4ca1063b73905","observation_id":"67430c67-b749-44c5-b785-ff7dabbc02f5","resolution":{"observed_at":"2026-08-12T16:59:33.594283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.585830Z","title":"A new method for retrieving band 6 of aqua modis,","venue":null,"work_id":"953bbf02-5c82-465e-b923-c8ec00c1e6d9","year":2006},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.186530Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:9e6b1d03d56255d6a91e3923b2b2b3c7d13864d82495508f68f45dfdf2aa618f","observation_id":"ae62a79f-bbc2-475b-9192-8c3b52a91581","resolution":{"observed_at":"2026-08-12T16:59:33.588555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.578732Z","title":"Restoration of aqua modis band 6 using histogram matching and local least squares fitting,","venue":null,"work_id":"1305b419-56ea-4146-98ea-9cab9f8a2cd0","year":2008},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.188409Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:3ba3e0f485860dbae91ecf0175a04656651b39de0f074d85e257ba0945ce3ec4","observation_id":"f5dc9092-18e1-46eb-8d74-8cea8bc1dd56","resolution":{"observed_at":"2026-08-12T16:59:33.581378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.572024Z","title":"Quantitative restoration for modis band 6 on aqua,","venue":null,"work_id":"03e55202-bc73-43f1-b884-5ff9a387de0d","year":2011},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.190292Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:b356dd4342bfe7ba6481db97e959473437fc701e3269899b118da1f5be9b6610","observation_id":"dc045c97-3e85-4a61-b4f4-1a61bf5e5453","resolution":{"observed_at":"2026-08-12T16:59:33.574668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.564684Z","title":"Thin cloud removal from optical remote sensing images using the noise-adjusted principal com- ponents transform,","venue":null,"work_id":"71ed5c15-add1-410d-aaef-6a0e33d80437","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.192260Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a85495bd28e704fce56add80ec3e46f674fcb0de1d17b605094d55cbbe07d38d","observation_id":"9f330034-d944-4d0c-9859-b157625dd969","resolution":{"observed_at":"2026-08-12T16:59:33.567359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.557973Z","title":"Block- gaussian-mixture priors for hyperspectral denoising and inpainting,","venue":null,"work_id":"b3d71594-56e2-4c06-8a2e-d8a9654663b8","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.194073Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:3274eff045f73ad92058e3042b5f05dabdbdbe333b32f9df1c62ee646da0bd22","observation_id":"9c42f123-620e-48ac-9f99-17361bbe1fa2","resolution":{"observed_at":"2026-08-12T16:59:33.560660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.551133Z","title":"Reconstructing modis lst based on multitemporal classification and robust regression,","venue":null,"work_id":"bce2b277-fa12-40b1-b1ea-86ca46d27064","year":2014},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.195909Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:51d77f0b887d7a659ce5fa4eab49104e2644d245ddbbad5c26d38c24f3e611a3","observation_id":"abc2ce22-5ff1-48cf-a85a-d15172049061","resolution":{"observed_at":"2026-08-12T16:59:33.553807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.544033Z","title":"A changing- weight filter method for reconstructing a high-quality ndvi time series to preserve the integrity of vegetation phenology,","venue":null,"work_id":"98f02351-b4dd-465a-b0ce-5d56e37f0a83","year":2011},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.197620Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:2b861c737c895cc576e730706b995d5221f62b7a7a23c5ab5826028419bcfece","observation_id":"1b4c086c-5ead-46a5-b934-0a579b8eb721","resolution":{"observed_at":"2026-08-12T16:59:33.546057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.538422Z","title":"Removing clouds and recovering ground observations in satellite image sequences via temporally contiguous robust matrix completion,","venue":null,"work_id":"fdf614e2-aaa4-4c68-b591-8af1eab4bc46","year":2016},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.199333Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:19556565ad54e7d575cffb700ac5659ea437f93e27ba97be52dd31f37016d113","observation_id":"3b0af98c-0e43-4f7f-8b35-f7cd4ea7ef3a","resolution":{"observed_at":"2026-08-12T16:59:33.540468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.532302Z","title":"Recovering quantitative remote sensing products contaminated by thick clouds and shadows using multitemporal dictionary learning,","venue":null,"work_id":"55c0e6e7-9455-4a83-90bc-93de1e244ad8","year":2014},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.201021Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:3a5f1f5530f240ee40b7d5b1d2dd30a180b3debcd06961fd16847d14289e4cbf","observation_id":"ac4940c2-7df3-4056-a4e6-54314da75476","resolution":{"observed_at":"2026-08-12T16:59:33.534688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.526321Z","title":"Thick cloud removal in landsat images based on autoregression of landsat time-series data,","venue":null,"work_id":"dcecf7e0-ab5f-460a-a885-895f85b5ea30","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.202773Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:c9ae71107e953722bd8a238410b6b484f7c870da75cf633df7e1cf1b70c47e3a","observation_id":"e770dc5d-2e57-4db3-b1ca-44e694f03098","resolution":{"observed_at":"2026-08-12T16:59:33.528379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.520185Z","title":"Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal mrf model,","venue":null,"work_id":"e536984b-9672-4140-a3dc-997aaea23bb7","year":2014},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.204471Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:79186c503a2ef1d656c7e9e963210a26b0dc34a7a5e3ec296f29ab5fbaf9e4d0","observation_id":"31f8f9b6-829a-462f-9c18-84b380ba8a39","resolution":{"observed_at":"2026-08-12T16:59:33.522290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.511814Z","title":"Contextual spatiospectral postrecon- struction of cloud-contaminated images,","venue":null,"work_id":"79ac5b06-fc5a-42cb-a91c-f1730e92e26f","year":2008},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.206446Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:297c7ad260df13dcc749701448fda9827308b237b5498034628fecbaa7e28b33","observation_id":"f39ce114-1626-4cf8-85c4-1a1ae163f381","resolution":{"observed_at":"2026-08-12T16:59:33.514668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.503401Z","title":"Sparse-based reconstruction of missing information in remote sensing images from spectral/temporal complementary information,","venue":null,"work_id":"82da763b-793b-4fa7-9b33-63db12b6af6f","year":2015},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.208844Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:719e19f8ca58a7b9d356c0089e9a1f24e673d9d67cbb44c7831e9c5f8db8c135","observation_id":"e7688ab5-5bea-4976-b8aa-e4cd26e1f805","resolution":{"observed_at":"2026-08-12T16:59:33.506271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.495343Z","title":"Spatially and temporally weighted regression: A novel method to produce continuous cloud- free landsat imagery,","venue":null,"work_id":"efddb719-54a7-4256-ac5b-5ad86d4c81cd","year":2016},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.211382Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:7f47ff6f396eb6f01befd432e947e442b4654b4deb1215627ca86db22f0a045d","observation_id":"2cefaf5c-c5de-4295-840a-ffaaa6666bb8","resolution":{"observed_at":"2026-08-12T16:59:33.498204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.487494Z","title":"Spatiotemporal reconstruction of land surface temperature derived from fengyun geosta- tionary satellite data,","venue":null,"work_id":"ad388cf0-effd-499b-a17a-21db30aa35e9","year":2017},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.213851Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:33a42f4f0718b5cc31107496daab396f3feeb72f159f1b505ea5718e31b02da5","observation_id":"57350e6c-1ce3-462c-a1d0-e407e64fb354","resolution":{"observed_at":"2026-08-12T16:59:33.490277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.479518Z","title":"Nonlocal tensor completion for multitemporal remotely sensed images’ inpainting,","venue":null,"work_id":"34c168d5-56c3-4efe-a37f-8a4dc7f49989","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.216340Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:3480015fd8baacab8f01df4e8d1307f9365fc91d58cdc693cf953b9dd0f93b1a","observation_id":"79e95ad0-e926-4acf-b80b-d47450b364f9","resolution":{"observed_at":"2026-08-12T16:59:33.482192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.473635Z","title":"Reconstructing cloud- contaminated multispectral images with contextualized autoencoder neu- ral networks,","venue":null,"work_id":"dd5befff-400c-4c04-9e87-c9da18a4cf20","year":2017},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.218794Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:0b06945182a084fcad4e7a239b6e93f2533e5818ce77d43af9c7c0bd23856581","observation_id":"fbfe0e5e-d67c-4cc8-83c2-d282844499a8","resolution":{"observed_at":"2026-08-12T16:59:33.475791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.221198Z","title":"Missing data reconstruction in remote sensing image with a unified spatial–temporal– spectral deep convolutional neural network,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.221198Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:86c78a30b91cf670edc81c6ebef56b4c992a4d0f9f03e5df3ae1f7d7b2d1a526","observation_id":"abc65462-2099-44b1-b920-513e46d2cb90","resolution":{"observed_at":"2026-08-12T16:59:33.221198Z","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":"2026-08-12T16:59:33.464142Z","title":"Reconstructing geostation- ary satellite land surface temperature imagery based on a multiscale fea- ture connected convolutional neural network,","venue":null,"work_id":"95f63de5-ee8b-46fd-98a9-6c90af19ef74","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.223622Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:b3b0ed8dcbe790040e2084c8a55dfed7326c4fa1e52024a79d56564ef328f9ea","observation_id":"9601cb64-5b58-4b21-8c23-337aeb372432","resolution":{"observed_at":"2026-08-12T16:59:33.466221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.457737Z","title":"Thin cloud removal with residual symmetrical concatenation network,","venue":null,"work_id":"5d8898ae-6911-4975-a2f6-49dc0d14acc5","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.226151Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:8ff2e2f3293de41fb43aaa1567313a4af17a3a16e6df30b9fe619e3b9a79fe92","observation_id":"83e53e7c-111e-41b6-bf3f-bb73b51d033f","resolution":{"observed_at":"2026-08-12T16:59:33.460445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.451821Z","title":"Thick clouds removal from multitemporal zy-3 satellite images using deep learning,","venue":null,"work_id":"bc175ec6-b9b9-4cd2-97b0-55885948c8be","year":2019},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.228279Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:f210aee0642ae9da5208119d1945d009bea71990fe33453a6380b50abec7213a","observation_id":"f942d09a-1214-4bd0-955e-7246ebdfd062","resolution":{"observed_at":"2026-08-12T16:59:33.453964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.445770Z","title":"Thick cloud and cloud shadow removal in multitemporal imagery using progres- sively spatio-temporal patch group deep learning,","venue":null,"work_id":"dc1db4a7-0e34-4c3e-a3ab-a1885ee2f08c","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.230630Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:18ee5eb18069a3761f7456bc782eb04d0f2e922e0d242e6f7988bc5dea09fb92","observation_id":"1a1cbccd-f5ea-48ef-8e8b-ee011ebea2a2","resolution":{"observed_at":"2026-08-12T16:59:33.448101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.437043Z","title":"Deep internal learning for inpainting of cloud-affected regions in satellite imagery,","venue":null,"work_id":"b4aeca59-8661-4fdc-bc1f-76248dd0cd00","year":2022},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.233030Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:d5fa3821ba1a992fee23249d3ac549542f1c7df81387d94f40e172a9597cfcae","observation_id":"787080df-5112-4139-b735-b9d21d5d8c01","resolution":{"observed_at":"2026-08-12T16:59:33.439800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.03432","last_updated":"2024-10-11T05:43:05Z","snapshot_observed_at":"2026-07-06T14:39:39.528087Z","submitted_at":"2023-01-09T15:31:28Z","title":"Multi-Modal and Multi-Resolution Data Fusion for High-Resolution Cloud Removal: A Novel Baseline and Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.03432","snapshot_observed_at":"2026-08-12T16:59:33.235439Z","title":"High-resolution cloud removal with multi-modal and multi-resolution data fusion: A new baseline and benchmark,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.235439Z"},"links":{"cited_paper":"/paper/2301.03432","citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:27734ec125075765b28a09f297ce52c41fa661720c5f9cb45c38406c987a14d4","observation_id":"1b4f568b-a886-4eae-a047-dd8d43acd282","resolution":{"observed_at":"2026-08-12T16:59:33.235439Z","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":"2026-08-12T16:59:33.428661Z","title":"Cloud-gan: Cloud removal for sentinel-2 imagery using a cyclic consistent generative adversarial networks,","venue":null,"work_id":"985f5007-ceff-44c9-804c-ac6e5414d4ee","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.238095Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:e1efc9bd1bc990ad14b185b7aff8f4f43cb960b086893ae7b595c55f5fcdba5c","observation_id":"0dd14292-8e62-4667-8b25-c19baa5f80c1","resolution":{"observed_at":"2026-08-12T16:59:33.431389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.420986Z","title":"A conditional generative adversarial network to fuse sar and multispectral optical data for cloud removal from sentinel-2 images,","venue":null,"work_id":"1a3b756a-0974-4486-bca6-9833b8b38326","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.240739Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:862731aebb1162ca057d7682fa41abe45a4c87988c86b68389013d9e26074651","observation_id":"a11a093b-8327-47ab-aaac-90e4b962ad82","resolution":{"observed_at":"2026-08-12T16:59:33.423809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.413741Z","title":"Restoration of sea surface temperature satellite images using a partially occluded training set,","venue":null,"work_id":"1d36e2e1-92cc-44ac-b9ff-dfcd08d2479e","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.243043Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a038735a0b52dce5ff932eb1e99356d83f771b3785ee805da49d084fde9e1dc5","observation_id":"92e87c44-13a1-4d67-b337-37d7f5ddb9c0","resolution":{"observed_at":"2026-08-12T16:59:33.416574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.405739Z","title":"Sar to optical image synthesis for cloud removal with generative adversarial networks,","venue":null,"work_id":"10a832a4-a149-4be9-a9e5-abeb356c8557","year":2018},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.245460Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:a6d1f3ee5336a3b50cb0ef8b6b0ad10b5dacfdc035b57dd8c52554d30d5e3972","observation_id":"68d2ff34-7d28-4f86-a680-ee9a226deec7","resolution":{"observed_at":"2026-08-12T16:59:33.409252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.399810Z","title":"Cloud removal with fusion of high resolution optical and sar images using generative adversarial networks,","venue":null,"work_id":"0f26b782-9397-44da-8245-e6739ffc90de","year":2020},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.247402Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:23ada1f2efbe2d3b6433074f3cba72c496d8577812987902121aa45e41abb632","observation_id":"8f7c9dac-6d75-4cdb-997f-4c3b439ea60c","resolution":{"observed_at":"2026-08-12T16:59:33.401874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.249304Z","title":"Glf-cr: Sar-enhanced cloud removal with global–local fusion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.249304Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:eec066a1942354299d8baf230132f0b5b958219f10146cb39862ab98b8cae5ee","observation_id":"d6ded80a-313a-4774-9628-9681d8993aeb","resolution":{"observed_at":"2026-08-12T16:59:33.249304Z","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":"2026-08-12T16:59:33.390140Z","title":"Ctgan: Cloud transformer generative adversarial network,","venue":null,"work_id":"1a3ed250-4d6e-4d0c-a602-9373ef4e6511","year":2022},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.250999Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:885d0c638e8d3b3bd2c3dd94ee4b98481d480716eb729be96f7c64be6df22fde","observation_id":"d90699ef-e64d-40c5-bc08-ae163b75ba78","resolution":{"observed_at":"2026-08-12T16:59:33.392301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16565","last_updated":"2023-08-08T16:01:41Z","snapshot_observed_at":"2026-08-02T20:58:15.270617Z","submitted_at":"2023-03-29T09:47:48Z","title":"PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite Imagery","version":2},"cited_work":{"arxiv_id":"2303.16565","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.16565","snapshot_observed_at":"2026-08-12T16:59:33.289597Z","title":"PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-performance Cloud Removal from Multi-temporal Satellite Imagery","venue":"cs.CV","work_id":"603a643f-8c7f-454c-b2c3-7c7198e057cb","year":2023},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.252803Z"},"links":{"cited_paper":"/paper/2303.16565","citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:234e95f575517426d785f808b31f425a4c0dce6676df4537ee28d182a980a14f","observation_id":"fc4c3ebb-bd2c-403d-baef-b793a7b61304","resolution":{"observed_at":"2026-08-12T16:59:33.294242Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.383683Z","title":"Attention is all you need,","venue":null,"work_id":"d94fc303-4856-4230-8939-e3ed284efd0b","year":2017},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.255003Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:255d63819aa723be11106dda0c56ac01a2c554c37c473563af4e7f5422a53fa0","observation_id":"154c691f-a465-4eaf-87b2-a3d0d5a7e117","resolution":{"observed_at":"2026-08-12T16:59:33.386032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.256922Z","title":"Rectified linear units improve restricted boltz- mann machines,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.256922Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:bb0183d11dd53915a38cd133ce8ab53b7a8a38152cdaf80b93fded091fad0b78","observation_id":"eed544ea-3806-443f-967b-19e4db6f1ad8","resolution":{"observed_at":"2026-08-12T16:59:33.256922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T16:59:33.258923Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.258923Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:6f45302227ba9bf214cfe543b6fcfc4cd6ebfd0657b0b0d0dbf11196f747448f","observation_id":"19d47664-97bb-4073-bbf8-7342ddcf85a8","resolution":{"observed_at":"2026-08-12T16:59:33.258923Z","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":"2026-08-12T16:59:33.370131Z","title":"Root mean square error (rmse) or mean absolute error (mae)?–arguments against avoiding rmse in the literature,","venue":null,"work_id":"17dc340f-ed54-4952-a389-0222fc994f8a","year":2014},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.260803Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:bfbc684de4e312bda15810d877f0d398f9f7156f11830bfb242184a3dee924c0","observation_id":"c70d221e-49f8-40d4-8426-2772a60d1133","resolution":{"observed_at":"2026-08-12T16:59:33.372286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.364066Z","title":"Peak signal-to-noise ratio revisited: Is sim- ple beautiful?","venue":null,"work_id":"8ad29bae-ceb5-4188-837d-84ee5720dfd8","year":2012},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.262541Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:f60298af6799c15c6f43987c6cf8fd825771ed13e437b5612f87ef181982d4e8","observation_id":"97dc7c75-ef9e-4748-9436-a8ac2653f515","resolution":{"observed_at":"2026-08-12T16:59:33.366217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.264229Z","title":"Image quality assessment: from error visibility to structural similarity,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.264229Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:98de1bc5f804fab58f9bf5ded6741847246999af01a87a1eec9a5aa0d2e7910a","observation_id":"2e64f421-1d4b-415e-98e6-63db9274e62f","resolution":{"observed_at":"2026-08-12T16:59:33.264229Z","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":"2026-08-12T16:59:33.352172Z","title":"The spectral image processing system (sips)—interactive visualization and analysis of imaging spectrometer data,","venue":null,"work_id":"a4c4ab56-35a8-4fc9-86db-6abd160cf682","year":1993},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.266061Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:33a8ef0f1cb4381dd2b85b606ffda0bccf282fbd45fb0e374ec4069114158529","observation_id":"8983cd7e-928e-40c0-885e-001f8388bf63","resolution":{"observed_at":"2026-08-12T16:59:33.355113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.344011Z","title":"Context adaptive network for image inpainting,","venue":null,"work_id":"217b1b00-d843-4ba4-97cd-e87873a93d15","year":2023},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.267809Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:548915360243a7ba4a70a054148e99f49720c916a48140ae9452424410d595a6","observation_id":"dd594482-5cb4-49f3-a93d-3d88d0d80086","resolution":{"observed_at":"2026-08-12T16:59:33.346867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.335677Z","title":"Restormer: Efficient transformer for high-resolution image restoration,","venue":null,"work_id":"1e6d8cb0-19a8-4f22-86bb-95b193c545cd","year":2022},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.269509Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:76f4fdde0cfa57ba2d51d88bc702a2a75925de03635390b78c8275d07105a37a","observation_id":"4355abad-8a70-4112-a218-bd81a0ae9fc2","resolution":{"observed_at":"2026-08-12T16:59:33.338620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T16:59:33.327548Z","title":"degree in the Institute of Artificial Intelligence and Robotics at Xi’an Jiaotong University","venue":null,"work_id":"c0c8490a-ac68-4898-a579-ec8e0e267893","year":2000},"citing_paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-12T16:59:33.271202Z"},"links":{"citing_paper":"/paper/2411.13042"},"observation_digest":"sha256:b44d0084e0303852290313e6245300903829655dc4852b3b1ee19edf33b772df","observation_id":"b0939f2f-11b4-4f37-9339-9dd8e164de76","resolution":{"observed_at":"2026-08-12T16:59:33.330602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.13042","last_updated":"2024-11-20T05:16:31Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T16:51:59.956834Z","submitted_at":"2024-11-20T05:16:31Z","title":"Attentive Contextual Attention for Cloud Removal"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":2,"verified_fuzzy":47},"total_outbound_references":58},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2411.13042."}