{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:ZDIU6BPZZ3ILZ24OO3GB7YYJ2D","short_pith_number":"pith:ZDIU6BPZ","schema_version":"1.0","canonical_sha256":"c8d14f05f9ced0bceb8e76cc1fe309d0db3977d4a2f54ea8d1d570b269d86b1d","source":{"kind":"arxiv","id":"2110.11661","version":2},"attestation_state":"computed","paper":{"title":"UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Vincent Lepetit, Wen Guo, Yang Xiao, Yuming Du","submitted_at":"2021-10-22T08:39:02Z","abstract_excerpt":"In this report, we introduce our (pretty straightforard) two-step \"detect-then-match\" video instance segmentation method. The first step performs instance segmentation for each frame to get a large number of instance mask proposals. The second step is to do inter-frame instance mask matching with the help of optical flow. We demonstrate that with high quality mask proposals, a simple matching mechanism is good enough for tracking. Our approach achieves the first place in the UVO 2021 Video-based Open-World Segmentation Challenge."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2110.11661","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-10-22T08:39:02Z","cross_cats_sorted":[],"title_canon_sha256":"9a5e56d4dca135e352e63ad506fe939021907a978d4eb8679b89b5f6787d471e","abstract_canon_sha256":"afbde74dd46b2d31d7bf0fe6768341a17731fff681b0bf0658d18b8877f85ec3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:27:59.198491Z","signature_b64":"wW8s+gzKsD2pbQLWpZQPriuIQHgF/Y6HEJ+d+OiNX5ptQZtSdlNfgTXKBAtYjz9UiYfyMizLDEl8pLfn50qFBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8d14f05f9ced0bceb8e76cc1fe309d0db3977d4a2f54ea8d1d570b269d86b1d","last_reissued_at":"2026-07-05T03:27:59.197950Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:27:59.197950Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Vincent Lepetit, Wen Guo, Yang Xiao, Yuming Du","submitted_at":"2021-10-22T08:39:02Z","abstract_excerpt":"In this report, we introduce our (pretty straightforard) two-step \"detect-then-match\" video instance segmentation method. The first step performs instance segmentation for each frame to get a large number of instance mask proposals. The second step is to do inter-frame instance mask matching with the help of optical flow. We demonstrate that with high quality mask proposals, a simple matching mechanism is good enough for tracking. Our approach achieves the first place in the UVO 2021 Video-based Open-World Segmentation Challenge."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.11661","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2110.11661/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2110.11661","created_at":"2026-07-05T03:27:59.198011+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.11661v2","created_at":"2026-07-05T03:27:59.198011+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.11661","created_at":"2026-07-05T03:27:59.198011+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZDIU6BPZZ3IL","created_at":"2026-07-05T03:27:59.198011+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZDIU6BPZZ3ILZ24O","created_at":"2026-07-05T03:27:59.198011+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZDIU6BPZ","created_at":"2026-07-05T03:27:59.198011+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D","json":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D.json","graph_json":"https://pith.science/api/pith-number/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/graph.json","events_json":"https://pith.science/api/pith-number/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/events.json","paper":"https://pith.science/paper/ZDIU6BPZ"},"agent_actions":{"view_html":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D","download_json":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D.json","view_paper":"https://pith.science/paper/ZDIU6BPZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.11661&json=true","fetch_graph":"https://pith.science/api/pith-number/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/graph.json","fetch_events":"https://pith.science/api/pith-number/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/action/storage_attestation","attest_author":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/action/author_attestation","sign_citation":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/action/citation_signature","submit_replication":"https://pith.science/pith/ZDIU6BPZZ3ILZ24OO3GB7YYJ2D/action/replication_record"}},"created_at":"2026-07-05T03:27:59.198011+00:00","updated_at":"2026-07-05T03:27:59.198011+00:00"}