{"as_of":"2026-08-16T09:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fad839cbd67984a76f8c7ef81bb72263805664da29a80394d04542605ad8f10c","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T15:06:25.376946Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.02021/citation-record","integrity":"/paper/1908.02021/integrity","json":"/paper/1908.02021/citation-record.json","paper":"/paper/1908.02021"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T15:06:25.816317Z","title":"Optimal point placement for mesh smoothing","venue":null,"work_id":"af3dd531-d8c9-4da0-98c9-c56febe2d2b4","year":1999},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.238235Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:b8668f856ae89c02ac212a3ed195634e47c63a9e2bf6e5992ba676cc301dc180","observation_id":"a87b97d8-4ea1-4f16-84a9-99fb2a84bfd6","resolution":{"observed_at":"2026-08-14T15:06:25.822170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.803022Z","title":"De- terministic consensus maximization with biconvex program- ming","venue":null,"work_id":"11ea51a6-a8ff-4327-bac3-74de3c90ec56","year":2018},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.243291Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:fe538a1e93afcc4fdf9adb915ceadfac7841a08d091a312422752a6e62993c09","observation_id":"ed35ec13-2aee-450c-81a6-97caf4728881","resolution":{"observed_at":"2026-08-14T15:06:25.807785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.789073Z","title":null,"venue":null,"work_id":"696ca9d7-c5d2-4854-94d2-c6f605b7c867","year":1966},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.248712Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:41b4b9d73d6690d06ba0bf9f18d7473b5f8fb27fd499284da954e7b9f3de5d73","observation_id":"bb43a8b2-4b47-4865-a6db-baeb165872d6","resolution":{"observed_at":"2026-08-14T15:06:25.793263Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.775044Z","title":"Robust fitting in computer vision: Easy or hard? In European Con- ference on Computer Vision (ECCV), 2018","venue":null,"work_id":"49bd1899-80c8-4836-af07-8dff66733e95","year":2018},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.253833Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:a0b1adeb8850463d805e22a6aa5c5fa35ffedad06112d223ddf9d81ff0867d44","observation_id":"89f4169c-c2db-4d64-961e-16c86f33bd42","resolution":{"observed_at":"2026-08-14T15:06:25.779876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.757317Z","title":"Efficient globally optimal consensus maximisation with tree search","venue":null,"work_id":"28e302c6-2d8d-4fc8-9ff8-5c32335df013","year":2015},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.258415Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:804489ed57074e35fdb3fb05abb2e63d076ede439411d2d988dd612b69ddbc74","observation_id":"36e8ff64-1960-47d9-af36-576a47c71bae","resolution":{"observed_at":"2026-08-14T15:06:25.762539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.742945Z","title":"Efficient globally optimal consensus maximisation with tree search","venue":null,"work_id":"103d8cf6-9a97-4c66-b13b-0d0a8f6bb025","year":2017},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.263385Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:0a5a1a877f9604b329c701f998338c88f05676b5129451d39581a37517dd6922","observation_id":"eddad740-c9cf-466d-8607-a6974b3329aa","resolution":{"observed_at":"2026-08-14T15:06:25.748118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.723718Z","title":"Matching with prosac- progressive sample consensus","venue":null,"work_id":"3a53e530-8b9e-445f-9ed6-ec1a2bb3202b","year":2005},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.268334Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:38511f28cb4b41717da22b39f4240d967678c404b77ab2dbcea9d8233e7699d5","observation_id":"ce899bfe-b5b7-4b8b-a8ad-c10b456258c4","resolution":{"observed_at":"2026-08-14T15:06:25.728295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.708241Z","title":"Locally optimized RANSAC","venue":null,"work_id":"0111fafb-1ce6-45eb-a1d1-5507e1077d37","year":2003},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.272844Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:20ff1c64889d6cf5f7509e71d22eb7d21e5f432e115f9b6f6f3cbc4845cb7cb3","observation_id":"75cb6249-d192-400b-ac52-59399d79292f","resolution":{"observed_at":"2026-08-14T15:06:25.713897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.692394Z","title":"Robust fitting for multiple view geometry","venue":null,"work_id":"00a1dc16-bc76-404a-9f36-fdbfd3e72261","year":2012},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.277597Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:c469665330bf53ac921c02fee65b1f6855f9da0a62b86595bf91d002e29be860","observation_id":"f96774a7-4c70-4c9f-96bb-42787bd020c6","resolution":{"observed_at":"2026-08-14T15:06:25.698023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.676879Z","title":"Quasiconvex programming","venue":null,"work_id":"d04cf275-98f4-4aa0-9abf-b51722d09ff4","year":2005},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.282091Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:78f0d6364e1bcf5cfd845435f1d4c8cac4e0b0769c03ba31776732f2089a575f","observation_id":"cf92fe9b-9ce8-4fe3-bf0e-da471dfc7790","resolution":{"observed_at":"2026-08-14T15:06:25.681483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.661472Z","title":"Fischler and Robert C","venue":null,"work_id":"c88f78b8-ac7b-473c-a19a-2afcd1daad42","year":1981},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.286925Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:9c849d573a47a4133ecb667c0b1b132d7568f3bcb2a502c079b3420d11a0595d","observation_id":"968eece8-88f7-4785-a937-60add262d4e8","resolution":{"observed_at":"2026-08-14T15:06:25.666132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.646704Z","title":"Are we ready for autonomous driving? the kitti vision benchmark suite","venue":null,"work_id":"ddc391d0-727b-46aa-8033-8838cd7ba439","year":2012},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.292887Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:1b894fad2196b781bfc4f31573ceb7fa01be5ee15dd51d4eb2a2a053ea7b130e","observation_id":"4654770e-6e8e-42e6-97b9-11a5ca9f440b","resolution":{"observed_at":"2026-08-14T15:06:25.651969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.630775Z","title":"Multiple View Ge- ometry in Computer Vision","venue":null,"work_id":"a40f9b49-7b34-484e-90f2-056e0202e11e","year":2003},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.299510Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:5e5b81b58921973fb697281b5003f2b3b261b793c22fbbe04e64078620ca12a6","observation_id":"07de2786-63b2-452b-8bf9-2af1106894ac","resolution":{"observed_at":"2026-08-14T15:06:25.636977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.617373Z","title":"An exact penalty method for locally convergent maximum consensus","venue":null,"work_id":"3ab1c4af-4840-48d4-a9b7-80216a859297","year":2017},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.304388Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:7c6ec2986ec32cd24eca11e589fb820d1acd9bec70e6e81504e6f56cdc574d19","observation_id":"b9a89a82-ceef-4ee5-820e-a4e2ba347189","resolution":{"observed_at":"2026-08-14T15:06:25.621849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.604675Z","title":"A practical algorithm for L∞ triangulation with outliers","venue":null,"work_id":"f2a1b9cf-09a0-47d3-a77a-8c8d6a07e0f9","year":2007},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.309405Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:c419f245fa843d7f64926c921d2dcae476a9800ccc33c6a16be9757b9d79cb51","observation_id":"920b9e32-5359-4deb-af33-44b8709a5bfb","resolution":{"observed_at":"2026-08-14T15:06:25.608932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.591751Z","title":"Consensus set maximization with guaranteed global optimality for robust geometry estimation","venue":null,"work_id":"5ac8c4d4-1dd4-4696-a4c6-14e79db8a503","year":2009},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.316264Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:5bd2d31b768046b65d0cf72b7228d81751c8c2b2b6d3754a7ebafb8c73ed2738","observation_id":"546b25a3-0b5f-494b-9f10-bbcab1b25a4a","resolution":{"observed_at":"2026-08-14T15:06:25.595968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.578228Z","title":"Object recognition from local scale-invariant features","venue":null,"work_id":"30a11498-7cb2-4132-bd3f-7df04ab5d580","year":1999},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.322053Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:c42ec21487c955c2245d07c60548fa76608aedf7b06380f77024f73fce4d77d3","observation_id":"276f7bbe-740f-484d-89cd-9b01d191f32d","resolution":{"observed_at":"2026-08-14T15:06:25.582576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.564336Z","title":"Matouˇsek","venue":null,"work_id":"9c68ff82-25a6-4239-b0ca-51d5851f63d9","year":1995},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.327503Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:0d33ca029b1a575d944220cdc28a47aad0657dd69bddf8b40a020476032dc0f4","observation_id":"a1768909-d684-45d3-8afd-d26369c56eac","resolution":{"observed_at":"2026-08-14T15:06:25.568758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.331752Z","title":"Numerical Optimization","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.331752Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:a4153afa5bc6e33caa00ed6c354f54b56ba47f0b05befb15aa925093a95b6ef8","observation_id":"178cfdcd-3fb6-4fa2-8944-e2aca3573eaf","resolution":{"observed_at":"2026-08-14T15:06:25.331752Z","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":"2026-08-14T15:06:25.539429Z","title":"A polynomial- time bound for matching and registration with outliers","venue":null,"work_id":"ca7f79ec-584e-4f39-a2a2-43771965b27e","year":2008},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.337585Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:041754f1f0facf26c4061de057b2ba1556e5093338044212733812c0e9fc4974","observation_id":"106e7335-9627-4ce2-9881-10c3c7a092fc","resolution":{"observed_at":"2026-08-14T15:06:25.544096Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.522821Z","title":"Efficient optimization for L∞-problems using pseudoconvexity","venue":null,"work_id":"96122d35-3c81-444f-877d-df93c22fe188","year":2007},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.343184Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:82ab85712db03d6e752e6764d42f07ff5431e7e19f5ac0455e8611f801670eb6","observation_id":"b59a819c-3f21-44f3-99ea-6355f6ef8d8f","resolution":{"observed_at":"2026-08-14T15:06:25.528337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.508546Z","title":"Guaranteed outlier removal for rotation search","venue":null,"work_id":"f45ea429-ad78-432a-ac27-7e2f52601870","year":2015},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.348457Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:024aca39c43c6a29cd61a77819906228d524a5569dbe744851686655c9dd36cf","observation_id":"80edf650-8853-4bfb-baef-8f5e2f6f4454","resolution":{"observed_at":"2026-08-14T15:06:25.512830Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.490597Z","title":"Maxi- mum consensus parameter estimation by reweighted L1 meth- ods","venue":null,"work_id":"cf6f255d-a696-42e6-bf42-b0757a09b381","year":2017},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.352815Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:e2c8eb31c4502efdff2f8625bbadc81e0c7f7d0e863397f866c035ba7715198e","observation_id":"31a5b9b9-00f0-47bb-957f-8f41b10add4d","resolution":{"observed_at":"2026-08-14T15:06:25.495913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.474838Z","title":"USAC: a universal framework for random sample consensus","venue":null,"work_id":"11fcb707-4077-462d-8143-ed4e6a485c3b","year":2022},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.357443Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:4748a9a937b5a5a955beddc7c74bc5b712759003abb5887fc8f8443f313b2d46","observation_id":"99fa6036-c740-4d77-9e5f-177ab65111b1","resolution":{"observed_at":"2026-08-14T15:06:25.479081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.459725Z","title":"A combinatorial bound for lin- ear programming and related problems","venue":null,"work_id":"b40c688d-1574-4afd-b4f8-f759bebc5be6","year":1992},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.362911Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:92c4d031efbd7d8ea943e23b3a102d7175507e03ecd5a6af494f5e2bd7a30cff","observation_id":"9ac36ba2-db3a-4b0b-8670-b534c2c06068","resolution":{"observed_at":"2026-08-14T15:06:25.464246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.443021Z","title":"Guided-MLESAC: Faster image transform estimation by using matching priors","venue":null,"work_id":"706fe05b-e56b-43c6-a732-28ab760d990a","year":2005},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.368243Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:72e90c729f9545a372c19760ffd77db3849bc25baf401cfaa91bc1a84b9c35e3","observation_id":"dff0ae90-10fe-4f56-9d8c-84cac83a18af","resolution":{"observed_at":"2026-08-14T15:06:25.448642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.428933Z","title":"VLFeat: An open and portable library of computer vision algorithms","venue":null,"work_id":"b7af25ba-d99e-4387-bd4b-efb40f7b5d52","year":2010},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.372533Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:868f6885ab0ae366bf839278ac3db9c4c9163ad9c81756aecb9b8375e19beba1","observation_id":"3d08ad98-9d19-4701-bba1-fa681dee47e0","resolution":{"observed_at":"2026-08-14T15:06:25.433684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T15:06:25.410480Z","title":"Deterministically maximizing feasible subsystems for robust model fitting with unit norm constraints","venue":null,"work_id":"4a902b80-6d81-4029-8417-499b9ecc2e7f","year":2011},"citing_paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T15:06:25.376946Z"},"links":{"citing_paper":"/paper/1908.02021"},"observation_digest":"sha256:be3b8ad02baec2c5831c41bf01b2058527e099107ce92f64f7fab13a16cb4ff0","observation_id":"f5a9048c-76ab-4148-a3c6-ab8086d6fcfe","resolution":{"observed_at":"2026-08-14T15:06:25.417823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.02021","last_updated":"2019-08-25T12:12:19Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T04:08:20.175902Z","submitted_at":"2019-08-06T08:54:04Z","title":"Consensus Maximization Tree Search Revisited"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":26},"total_outbound_references":28},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:1908.02021."}