{"as_of":"2026-08-19T14:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b999c47b2b3fef36db130beedd2914fe80d602050e22444d937c702464f62ebc","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T05:43:57.193424Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1909.00781/citation-record","integrity":"/paper/1909.00781/integrity","json":"/paper/1909.00781/citation-record.json","paper":"/paper/1909.00781"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.156064Z","title":"Playing for data: Ground truth from computer games,","venue":null,"work_id":"9710b4f2-8ea9-4fa6-b0af-55537ae29daf","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.900552Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e54a2bd34d4ae1165d6ba68bc4149e879e2ef05c216ecb9d3e0ff0c0ae708538","observation_id":"169085cf-3e9c-4ca1-b8fd-f34ce556fe6f","resolution":{"observed_at":"2026-08-14T05:43:58.161082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.141195Z","title":"The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes,","venue":null,"work_id":"d3bc7bb0-1e36-4cb2-84db-eb701fa2af00","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.905901Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:c02acda98d70b443dcfd6ce6e47a7a54ea5ef87cfed1b2670815d375c59197b4","observation_id":"bf5476bd-a138-4512-b8eb-3dd7b0dd16cf","resolution":{"observed_at":"2026-08-14T05:43:58.146281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.124440Z","title":"Unsupervised Domain Adaptation for Semantic Segmentation of Urban Scenes,","venue":null,"work_id":"cf891781-8cbb-4290-84f0-d22192458748","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.911341Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:ddd9c55246aa19596ea0fe4a660821b0b14e1992186cdcbd9bd9e3df9d4a6801","observation_id":"2f0e38c9-d2f2-462f-8dca-46b895c5ec51","resolution":{"observed_at":"2026-08-14T05:43:58.130311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.108014Z","title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,","venue":null,"work_id":"7619620e-1af0-4ea6-9ca8-baa212d68c13","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.916439Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:8884833ea8066914b73d212dcf3dc785ef4a93278fd99b28730d17b31875d539","observation_id":"9c1b5925-6ed6-4366-aae0-19ffc23c94d1","resolution":{"observed_at":"2026-08-14T05:43:58.113157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.092192Z","title":"Adversarial learning for semi-supervised semantic segmentation,","venue":null,"work_id":"50860f4c-8aa9-4c23-8677-c4bdc15beeb0","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.921233Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:3a1c04ca04894f2c8675875fca94c7b9955548070d3e0f874f02b9a2bb8063b5","observation_id":"7e30712c-dcc7-48f9-bd3c-2b5c20d865a0","resolution":{"observed_at":"2026-08-14T05:43:58.097712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.076498Z","title":"Semi- supervised automatic segmentation of layer and fluid region in retinal optical coherence tomography images using adversarial learning,","venue":null,"work_id":"9766cc4b-121e-465f-a000-d17484d72e93","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.926090Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:3df4bb9be6fafa526c2f6fe82a52bf5788fce1999a199f5117046888cecb6a55","observation_id":"f8b635ef-0f9e-4cae-942b-9d5b73f651c3","resolution":{"observed_at":"2026-08-14T05:43:58.081464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.061426Z","title":"A survey on deep learn- ing techniques for image and video semantic segmentation,","venue":null,"work_id":"c2c4814f-cd85-4f3e-ac3a-7fb26e5a6606","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.931524Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:8f670e2ce324874c779872f8b583c7565dada52784333e7dde041c557da94b0d","observation_id":"75230b47-4310-40a8-bbb9-a64b7017c5a2","resolution":{"observed_at":"2026-08-14T05:43:58.066320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.045829Z","title":"Fully convolutional networks for semantic segmentation,","venue":null,"work_id":"0c85ad93-c9aa-4060-8729-c39b48835cc6","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.936051Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:c463dcdd3262a99b2026182b0116da10a5e57bf0141d54374651ae9348166506","observation_id":"ff787ea2-abc0-40c1-bced-b64fe0db34f9","resolution":{"observed_at":"2026-08-14T05:43:58.050830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:56.941657Z","title":"Multi-scale context aggregation by dilated convolutions,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.941657Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:398ddd401bc2d6ce97c05fa89f4b8ed214ebd34e0c0bb5d73833818cb5fb4c40","observation_id":"b1895488-989b-4495-8340-c81db64a79f0","resolution":{"observed_at":"2026-08-14T05:43:56.941657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.020747Z","title":"Pyramid scene parsing network,","venue":null,"work_id":"d778221b-070d-458e-b939-da9b085ca225","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.946240Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:023a051f31513e9ab77382974dfac1492d859166f61b54820fd71e6391974d13","observation_id":"015c8adb-bfe1-4223-96fa-8a73b587e8db","resolution":{"observed_at":"2026-08-14T05:43:58.025620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:58.005805Z","title":"Crdoco: Pixel- level domain transfer with cross-domain consistency,","venue":null,"work_id":"3164e34b-f206-456b-b0fc-461d579830ba","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.950736Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:a8908a91c854b8b83779c46a51b55fdca9b41eaf51856735442ba17b76631b82","observation_id":"328de90d-7821-4efd-955e-d81141818037","resolution":{"observed_at":"2026-08-14T05:43:58.010546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.989834Z","title":"Game theoretic analysis of road user safety scenarios involving autonomous vehicles,","venue":null,"work_id":"b23a605a-1289-49df-99f3-79e18ce3b004","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.955643Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:f21e4ed0cda171e048e676d4b92530f9e4a58a902f4ebe719106b72f69811281","observation_id":"7e1393f0-705d-41a9-8433-80823ebb87c6","resolution":{"observed_at":"2026-08-14T05:43:57.995716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.974698Z","title":"The Cityscapes dataset for semantic urban scene understanding,","venue":null,"work_id":"2b7a4037-2c90-4ace-9c6a-fc3f635f3649","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.961117Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:a2ac24d2791c5ba91bdcbe7073dec51cd4dd296757d60a05c643e963e27a5960","observation_id":"9d269867-684b-4409-ac4b-650a441ca32c","resolution":{"observed_at":"2026-08-14T05:43:57.979747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.958702Z","title":"The Mapillary vistas dataset for semantic understanding of street scenes,","venue":null,"work_id":"db144027-bce3-4df8-ac30-0695ef8309e4","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.965452Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:22df1a0a707dcca95c53b521b2ed5e85b56076ffb930115c80bbceecf0f5fded","observation_id":"fe8af1f3-16fb-4f14-9b74-1666e5b23ad8","resolution":{"observed_at":"2026-08-14T05:43:57.963786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.04687","last_updated":"2020-04-08T09:25:06Z","snapshot_observed_at":"2026-08-14T19:16:08.121001Z","submitted_at":"2018-05-12T09:24:21Z","title":"BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.04687","snapshot_observed_at":"2026-08-14T05:43:56.969985Z","title":"Bdd100k: A diverse driving video database with scalable annotation tooling,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.969985Z"},"links":{"cited_paper":"/paper/1805.04687","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:b743bb3edc54ace8f04fff8598679c64460b3963cd1382fe185930aa256e8e5e","observation_id":"6154087f-5de5-4b8a-bcfd-9de01e1ecf4e","resolution":{"observed_at":"2026-08-14T05:43:56.969985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.943710Z","title":"Curriculum domain adaptation for semantic segmentation of urban scenes,","venue":null,"work_id":"f590dfa2-e725-43c4-b64c-5f44765e6cba","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.975479Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:67667cf37b283a074ac47b16e549eece51a59ee0a4aaeb9302cc652687b927e1","observation_id":"c27f657f-cbaf-4aa6-bcb7-d004d9c45031","resolution":{"observed_at":"2026-08-14T05:43:57.948543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.927708Z","title":"Road: Reality oriented adaptation for semantic segmentation of urban scenes,","venue":null,"work_id":"0c1045eb-e0b8-4304-a91f-b3677be9c1c1","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.980011Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:4d6e9b1439d2b04fbadaff8f363062f2f260ff2e8222617f83b2d2c347801fb7","observation_id":"b0273549-b6a7-4610-946a-ce02634fdcb9","resolution":{"observed_at":"2026-08-14T05:43:57.932987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.911976Z","title":"Attribute dissection of urban road scenes for effi- cient dataset integration,","venue":null,"work_id":"b114c3e3-8709-4540-b519-96bd24c764b8","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.984550Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:3998d5dff370e544c1f62e8bca2be2d74626ddd2f08fb3af35cbfa2eb153f911","observation_id":"c5cbbc3e-7b52-4c76-b4fe-e7f9d4c80fdd","resolution":{"observed_at":"2026-08-14T05:43:57.917011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.897514Z","title":"Semantic object classes in video: A high-definition ground truth database,","venue":null,"work_id":"04e28f38-143b-485a-b775-564a48c61fb6","year":2009},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.989017Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:32ec93e16e3a280af1fb6762e9f78d55d656359c65a48adaac3ef6f62b4ccf18","observation_id":"60290883-bee0-413f-a593-ea4105c76c2d","resolution":{"observed_at":"2026-08-14T05:43:57.902344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.882611Z","title":"Constrained convolutional neural networks for weakly supervised segmentation,","venue":null,"work_id":"79833358-4316-408f-b6c0-e3ed4511ff1d","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.993579Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:bfb0f757a9c8471e6f1e507dd69adb288d2e48fd709e15b4774be2225181c7c6","observation_id":"ffe1f12e-e863-4151-8ca1-4ccafb27aea4","resolution":{"observed_at":"2026-08-14T05:43:57.887617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.09695","last_updated":"2017-03-28T17:57:21Z","snapshot_observed_at":"2026-08-19T10:41:56.265597Z","submitted_at":"2017-03-28T17:57:21Z","title":"Semi and Weakly Supervised Semantic Segmentation Using Generative Adversarial Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.09695","snapshot_observed_at":"2026-08-14T05:43:56.998497Z","title":"Semi and weakly supervised semantic segmentation using generative adversarial network,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:56.998497Z"},"links":{"cited_paper":"/paper/1703.09695","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:201ae759ede7d958ebfb101d7f56edf83c7ee8c389de5a54a647782cedfd5900","observation_id":"f7004cef-8f23-40a5-9d4c-20883168ae31","resolution":{"observed_at":"2026-08-14T05:43:56.998497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.867783Z","title":"Towards weakly supervised seman- tic segmentation by means of multiple instance and multitask learning,","venue":null,"work_id":"c12a18bc-273a-4228-ba3c-6502ff198429","year":2010},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.003778Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:631744447659ba8ab989338180841c43c9026a4767b3ffdc831eee3322692753","observation_id":"ea3f6c11-2a05-4194-abe3-c7fe4dd2f32b","resolution":{"observed_at":"2026-08-14T05:43:57.872568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.852923Z","title":"STC: A simple to complex framework for weakly-supervised semantic segmentation,","venue":null,"work_id":"65f1603b-45ff-4a75-9dfc-5aeba0887d6b","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.008534Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:2281085ed6422040b50e489f4df10a31e0768283082e9242263f7267a09327f4","observation_id":"55812083-a235-4880-bb41-22d6275bfb6c","resolution":{"observed_at":"2026-08-14T05:43:57.858126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.838171Z","title":"Decoupled deep neural network for semi- supervised semantic segmentation,","venue":null,"work_id":"a31674a3-8846-42cf-8f72-a8032251edf8","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.012804Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:f5a7b24325817cae036d9fc6518e3aa794e07208df5900336485aa84598f6f23","observation_id":"bae0368d-ee8e-4691-bd0e-d263944ddacf","resolution":{"observed_at":"2026-08-14T05:43:57.843004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.823275Z","title":"Boxsup: Exploiting bounding boxes to super- vise convolutional networks for semantic segmentation,","venue":null,"work_id":"4980e346-59ad-48ed-980e-6b64ffb116ba","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.018142Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:8710619106b0d6a70ae964005258dbd0a115a4d33fe8550824ad5c97949ecf13","observation_id":"e534f6bd-9c32-4714-b355-4bb9f480ea76","resolution":{"observed_at":"2026-08-14T05:43:57.828287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.808349Z","title":"Weakly-supervised semantic segmentation network with deep seeded region growing,","venue":null,"work_id":"041d7cd4-0cd2-4b6c-8477-e619975d24da","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.022580Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:84dcd23fe0680b03e17f1429fdcd1b0f1dea4e2f06f2912a66470f4ea7303da3","observation_id":"eac3d034-5330-4062-a851-9c15e0c37c4b","resolution":{"observed_at":"2026-08-14T05:43:57.813093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.793473Z","title":"Saliency guided deep network for weakly-supervised image segmentation,","venue":null,"work_id":"905f21e3-e7b8-464b-9081-458261654c88","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.026677Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:37f6e5f7c5ed3a5296f8b2a267337f1a345624e0d02c1c659f1fe8346bc0bf6b","observation_id":"93c2608a-9b2a-49b9-963c-6c11f37212c0","resolution":{"observed_at":"2026-08-14T05:43:57.798147Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.778961Z","title":"Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation,","venue":null,"work_id":"eee2f918-2c28-453b-b2ef-39839d668e0b","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.031505Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:c4565decc67cccb5702688711c073358e06c4549fd85247ecd9648c14efd5217","observation_id":"2cbdc880-ab29-4b8d-8c27-7fba8556929e","resolution":{"observed_at":"2026-08-14T05:43:57.783957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.763120Z","title":"Learning from synthetic data: Addressing domain shift for semantic segmentation,","venue":null,"work_id":"f70a9dad-1046-4e4e-8443-d4ced19f5e08","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.036657Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:0f05adb9e4a0cf1435f5014425ffc71cb94ad837f0cfa3a0b7431ab2c24dfc40","observation_id":"c4f4c573-8947-485d-ac08-58f713f84678","resolution":{"observed_at":"2026-08-14T05:43:57.768866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.746994Z","title":"Semantic segmentation using adversarial networks,","venue":null,"work_id":"21b22a8e-c940-48de-9931-fe9c245504ef","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.041413Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:a4e4ea317defa28c156695ded16f05def9f23be353802705069391a09dcc5c70","observation_id":"b62b1aa4-8af6-4dbd-a9fd-112e1fb474bf","resolution":{"observed_at":"2026-08-14T05:43:57.751979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.731589Z","title":"A deeper look at dataset bias,","venue":null,"work_id":"1f65f851-d6ef-456b-aa76-cb0638291fd9","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.045848Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e2aadaaf7f9dae6bfb8c71c180af13821fff24c7eb04ffe0e042a6feccab82d0","observation_id":"dbef8cf0-31e4-496e-98f4-4367607893eb","resolution":{"observed_at":"2026-08-14T05:43:57.736530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.716033Z","title":"Unbiased look at dataset bias,","venue":null,"work_id":"f00b9a57-0127-4f9c-9b0a-3200e40c518f","year":2011},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.050253Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:6bd264be82aa0176a216b2dee2364f9ba4dc2c79afbf18f1071c61179caf666f","observation_id":"fc44bacd-28ed-4de9-8fe6-387b964a3af2","resolution":{"observed_at":"2026-08-14T05:43:57.721379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.701147Z","title":"Overcoming dataset bias: An unsupervised domain adaptation approach,","venue":null,"work_id":"b0d420a2-f5d0-4dc0-a5f3-a1af0acde3bf","year":2012},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.057738Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:c8c9049510502ad4eb3fb32e5641ae4bbd9bb4638f0a3d7e21c3c7d0e9bdef0c","observation_id":"20140bcb-18d5-4c3e-be8a-5804c08f97ac","resolution":{"observed_at":"2026-08-14T05:43:57.706196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.684958Z","title":"Undoing the damage of dataset bias,","venue":null,"work_id":"1c9ab5f3-b091-4f3e-a066-55dcefb770aa","year":2012},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.062249Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:cda4e685d9a941356d3e5d736b328f7fed1fa3686f03768ba214fe661d8d9175","observation_id":"ade7139f-1171-41a9-b768-26df5cbf2e8d","resolution":{"observed_at":"2026-08-14T05:43:57.690283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.669067Z","title":"Learning from simulated and unsupervised images through adversarial training,","venue":null,"work_id":"94fed632-c7aa-4119-9f5c-3e14fed5b567","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.066555Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:435c1871c9f192b19074841d87a93e82550434f882e0375f9716e7b0a8f63d3c","observation_id":"ad997f57-293d-4715-bc3b-bb60ec2744d1","resolution":{"observed_at":"2026-08-14T05:43:57.673785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.653927Z","title":"Synthetic to real adaptation with generative correlation alignment networks,","venue":null,"work_id":"86c89b37-04de-4c40-bd26-8b1d8b9c81b7","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.071275Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:059bd3b88b2948c262faa7ee2dbb083a03440b8d1e054869368bb4ee139f9d0a","observation_id":"e4fd0ee7-98ea-4dac-adaa-6c21c54921f6","resolution":{"observed_at":"2026-08-14T05:43:57.658912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.638862Z","title":"Generative image modeling using style and structure adversarial networks,","venue":null,"work_id":"2830ff7a-8192-4a27-ba4d-81b6780a1df2","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.076242Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e3444421a061d8c67fb6695ff9e5c1018f3ec378b80ddb21a1931b7bf26f9afc","observation_id":"760af95a-ee91-4bdf-a14c-9cf32a246dd3","resolution":{"observed_at":"2026-08-14T05:43:57.643544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.623311Z","title":"Generative visual manipulation on the natural image manifold,","venue":null,"work_id":"737d69f6-6ad2-4758-9bce-878020b7f532","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.081009Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:aee8a69fe970b274581a768d6192b3174c555db52d4cd7af239abd0372e77e58","observation_id":"1e0e8b11-fdef-4f87-93e8-9420accc88f7","resolution":{"observed_at":"2026-08-14T05:43:57.628856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1602.05110","last_updated":"2016-12-13T03:21:03Z","snapshot_observed_at":"2026-08-14T22:10:06.307171Z","submitted_at":"2016-02-16T17:51:39Z","title":"Generating images with recurrent adversarial networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1602.05110","snapshot_observed_at":"2026-08-14T05:43:57.085609Z","title":"Generating images with recurrent adversarial networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.085609Z"},"links":{"cited_paper":"/paper/1602.05110","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:22d66ebc0d88309d79e7565614cf8a6b7c9a6d292800c45d39945b1967bf9ec8","observation_id":"e5712674-2c0d-45c4-bfab-ac6651451a71","resolution":{"observed_at":"2026-08-14T05:43:57.085609Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.607389Z","title":"Weakly supervised object localization with progressive domain adaptation,","venue":null,"work_id":"12a5d962-c478-4dc0-892f-a39eee1d8e1a","year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.090619Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:8a4402b607b6a20fc4a4743ec0355c34b6b49f52bb5fd50eb5064bae20ee5326","observation_id":"7a1eb6f2-3c67-4240-8067-a73ee2b144b6","resolution":{"observed_at":"2026-08-14T05:43:57.613021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.095508Z","title":"Cross-domain weakly-supervised object detection through progressive domain adap- tation,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.095508Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:347fcbf73cdbc64d1a5e8a11e027b13c89b63cfc2456f844bfb69edce22be9e2","observation_id":"0e1b3610-d58f-4460-a9de-188a22be50ae","resolution":{"observed_at":"2026-08-14T05:43:57.095508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.582145Z","title":"Unified deep supervised domain adaptation and generalization,","venue":null,"work_id":"837ed0cd-1bae-495b-bba1-5df205c20f79","year":2017},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.100260Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:3f0d93c45cbdec6edf1a58c6785b2a8faa1fc26c20abedcf8b34e667ba9ffe68","observation_id":"52f3bd18-18a0-4422-a5c0-4a9973f71536","resolution":{"observed_at":"2026-08-14T05:43:57.587616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.06487","last_updated":"2019-09-14T18:06:46Z","snapshot_observed_at":"2026-08-14T16:47:08.336834Z","submitted_at":"2019-04-13T05:33:46Z","title":"Semi-supervised Domain Adaptation via Minimax Entropy","version":5},"cited_work":{"arxiv_id":"1904.06487","doi":null,"metadata_source":"pith","pith_arxiv_id":"1904.06487","snapshot_observed_at":"2026-08-14T05:43:57.261224Z","title":"Semi-supervised Domain Adaptation via Minimax Entropy","venue":"cs.CV","work_id":"580f2920-69a4-4789-b161-bf61f2cb3613","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.105056Z"},"links":{"cited_paper":"/paper/1904.06487","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e4c31d202ae990be77aedd02ba4eb5723c9e8872ac064df2973b71541012294b","observation_id":"b0250e45-f31f-4160-bffe-def23f263ead","resolution":{"observed_at":"2026-08-14T05:43:57.269175Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.565331Z","title":"Unsupervised domain adaptation by backpropagation,","venue":null,"work_id":"d365eda5-66b9-48ea-8244-0f34c5b279ea","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.110537Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:243a22eb945c6f72bcf72792a7047741df0aad0288142eee005417c4ba155f4f","observation_id":"21a8e158-66db-4f04-b1a2-81e915509848","resolution":{"observed_at":"2026-08-14T05:43:57.571245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.115336Z","title":"Domain-adversarial training of neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.115336Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:6661ed48296b97249af349d8c6b5c490d93be1acf9b98e1e8b9678f2d57ad537","observation_id":"d323a685-1d6d-4b60-a5a6-b5f3e91b78cb","resolution":{"observed_at":"2026-08-14T05:43:57.115336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.540239Z","title":"Learning transferable features with deep adaptation networks,","venue":null,"work_id":"bd93b858-d7be-451d-89b8-73a3c6517a12","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.119866Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:20754cee9858f07d3cdaa4984c25dac51c143c3f53b100b00091269041fd7618","observation_id":"5cccff9e-60e0-4f4f-b8cd-68b1fd16acdb","resolution":{"observed_at":"2026-08-14T05:43:57.545092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.525921Z","title":"Simultaneous deep transfer across domains and tasks,","venue":null,"work_id":"50667552-591e-4ca8-9efc-ba1c5209f0fb","year":2015},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.124429Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:fd93741ba7473064f509991847b65baefbbec25ddab7b42c06d0f50d1d5ca8d5","observation_id":"86695cbf-440b-49fb-8aed-ad0ec3f35b14","resolution":{"observed_at":"2026-08-14T05:43:57.530578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1612.02649","last_updated":"2016-12-08T14:11:10Z","snapshot_observed_at":"2026-08-14T21:26:29.466258Z","submitted_at":"2016-12-08T14:11:10Z","title":"FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.02649","snapshot_observed_at":"2026-08-14T05:43:57.129188Z","title":"FCNs in the wild: Pixel-level adversarial and constraint-based adaptation,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.129188Z"},"links":{"cited_paper":"/paper/1612.02649","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:4434b6e8a6b42289f0e289bf9777cd298e74867e7de320790ef43dbdab78c556","observation_id":"9d632d42-8805-4075-a8d9-194fd1668fbe","resolution":{"observed_at":"2026-08-14T05:43:57.129188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.511284Z","title":"Unsupervised domain adaptation for tof data denoising with adversarial learning,","venue":null,"work_id":"9b9eed3d-0eff-4731-a355-cb6fabc792d0","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.133973Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:55c628d72af0676670cc665b5614d1297a1f931b5fbc6ae90627f0e94b42a4bc","observation_id":"f08613e9-1b10-4926-a24a-18470f020202","resolution":{"observed_at":"2026-08-14T05:43:57.516073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.496525Z","title":"Learning to adapt structured output space for semantic segmentation,","venue":null,"work_id":"586b2d53-58fd-481b-99aa-17af468eef5a","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.138457Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:1fb9c010ed5e6d2082634a173e24a157c2dd3f1fcf4ef24a7ab1b6c1e1d7365b","observation_id":"2b21e0d1-5533-44f1-b228-954147495479","resolution":{"observed_at":"2026-08-14T05:43:57.501401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.481439Z","title":"Taking a closer look at domain shift: Category-level adversaries for semantics consistent domain adaptation,","venue":null,"work_id":"da8a1c1a-7faf-4a6a-a446-02602e8b4a55","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.142789Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e0204441c3bab11c51708c5df58a69515e6d4d89255b94613df6b1cd6b69c4a0","observation_id":"34bf4a14-1547-4725-a04d-058845ddd509","resolution":{"observed_at":"2026-08-14T05:43:57.487063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.466099Z","title":"Incremental Learning Techniques for Semantic Segmentation,","venue":null,"work_id":"65503356-989f-4847-ab6e-1ef0d40c2e3c","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.147456Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:b7712a3149fd00d56fae2f0b959d458ef1d6f4e1e0e3381d806a2b6037c8cab8","observation_id":"087619a5-0232-441f-8e71-420d9004ba20","resolution":{"observed_at":"2026-08-14T05:43:57.470777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.450889Z","title":"Unsupervised domain adaptation for semantic segmentation via class-balanced self-training,","venue":null,"work_id":"3483064d-f661-463b-a1d6-45a26a5ef193","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.151959Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:2d69e4b4816cea254b1742bb75c1c1a512ac668e080ea6fd153679fe883580e7","observation_id":"5ebe5af5-5bf9-4524-99ec-92143b53e37f","resolution":{"observed_at":"2026-08-14T05:43:57.455800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.435719Z","title":"Penalizing top performers: Conservative loss for semantic segmentation adaptation,","venue":null,"work_id":"6ae4fffd-214d-423c-bac1-ac6ad884aec8","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.156547Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:c187927d771f0744b34c8714899eb234bb9b0b120298d98f668003f287cf9727","observation_id":"fd433567-a889-44d1-850a-829c2b98cb3c","resolution":{"observed_at":"2026-08-14T05:43:57.440717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1812.05040","last_updated":"2019-01-13T23:49:13Z","snapshot_observed_at":"2026-08-14T17:44:39.341924Z","submitted_at":"2018-12-12T17:23:24Z","title":"Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.05040","snapshot_observed_at":"2026-08-14T05:43:57.161148Z","title":"Learning semantic segmentation from synthetic data: A geometrically guided input-output adaptation approach,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.161148Z"},"links":{"cited_paper":"/paper/1812.05040","citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:37691a2f11406ba96a106dfdeb641c19686a39bc92fdcb40b2f3db2e25ca7bb9","observation_id":"0c322283-663d-4370-89da-ee5b3b950d38","resolution":{"observed_at":"2026-08-14T05:43:57.161148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.419512Z","title":"Fully convolutional adaptation networks for semantic segmentation,","venue":null,"work_id":"d63f3eb4-a6ce-419f-baf7-577ba29777a3","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.166186Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:2f0d68ddb77247dfd0d52ee17701aa696231037da8ce9ef63d14b4a910e3b065","observation_id":"8e214cf4-4912-4506-bf0c-add8b1ae7242","resolution":{"observed_at":"2026-08-14T05:43:57.424288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.403244Z","title":"Advent: Adversarial entropy minimization for domain adaptation in semantic segmentation,","venue":null,"work_id":"52cebb33-420c-4cab-90b5-e5613e98fbd3","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.170792Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:e3f68a39cb97b6d32550863ccd091140628624a13ff4f2674b7c96756475fbea","observation_id":"cbd43f6b-0d4d-4d53-bc9c-450d6379f40b","resolution":{"observed_at":"2026-08-14T05:43:57.408596Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.386068Z","title":"Cycada: Cycle-consistent adversarial domain adapta- tion,","venue":null,"work_id":"2835a4dc-0395-4833-a61f-2e48d4a3166f","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.175090Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:d9be803d1b601cf79e4b14c384210fcee4d5a8099775babfc9db91c341a22d5e","observation_id":"7bd9c7bf-b380-4fa7-bab4-db31e7f1a8d1","resolution":{"observed_at":"2026-08-14T05:43:57.390841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.371132Z","title":"Seeded region growing,","venue":null,"work_id":"0bda98fd-4c10-433d-bbdb-845a98dc6d79","year":1994},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.179548Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:6e0135f4885fcc2a689e8768e7adc01be6db8acdd74efd146dcd5a4cf85e55d7","observation_id":"f5daebf5-0480-46cf-b357-e8583690a144","resolution":{"observed_at":"2026-08-14T05:43:57.376008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.355275Z","title":"Seednet: Automatic seed generation with deep reinforcement learning for robust interactive seg- mentation,","venue":null,"work_id":"1aee5581-0e4b-42d8-9f30-eb45ea55c6ef","year":2018},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.184280Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:4187adb2e75f9f15b33b9b1f6eb059ebacb83b36496d95091ace9e1bbb74b638","observation_id":"1d86b64b-2daf-44ec-af8b-46834ba8a798","resolution":{"observed_at":"2026-08-14T05:43:57.360164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.340095Z","title":"Pre-computed weights for ResNet-101,","venue":null,"work_id":"8ef77ffd-5b26-4602-b8e0-6d55124c5301","year":2019},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.188802Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:9fbd6c7aeef3a568ebf15e4fb087db04d37d8a50ef794bb045d3ec479e25ab86","observation_id":"e98163ed-475f-4a47-a0dc-25ca8fc5336f","resolution":{"observed_at":"2026-08-14T05:43:57.344739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T05:43:57.325226Z","title":"Microsoft coco: Common objects in context,","venue":null,"work_id":"9e355a45-bd70-4a27-900f-a0b85c372399","year":2014},"citing_paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T05:43:57.193424Z"},"links":{"citing_paper":"/paper/1909.00781"},"observation_digest":"sha256:cbbd66fa97d2ea6478a0ab39327cc6d06e88e0179c9f372e58b0f2740b7ac4b2","observation_id":"95d0d205-45be-46e7-8578-ca7887538e84","resolution":{"observed_at":"2026-08-14T05:43:57.329959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1909.00781","last_updated":"2020-03-02T15:46:24Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T03:25:53.939460Z","submitted_at":"2019-09-02T16:05:05Z","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":53},"total_outbound_references":62},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:1909.00781."}