{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:XG75QSHCUIVYZ66WWTG6DVF2BE","short_pith_number":"pith:XG75QSHC","schema_version":"1.0","canonical_sha256":"b9bfd848e2a22b8cfbd6b4cde1d4ba09150b37bb9f030109675de7a7411b976d","source":{"kind":"arxiv","id":"2003.00482","version":1},"attestation_state":"computed","paper":{"title":"State-Aware Tracker for Real-Time Video Object Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Donglian Qi, Gang Yu, Jianxin Shen, Xi Chen, Ye Yuan, Zuoxin Li","submitted_at":"2020-03-01T12:48:20Z","abstract_excerpt":"In this work, we address the task of semi-supervised video object segmentation(VOS) and explore how to make efficient use of video property to tackle the challenge of semi-supervision. We propose a novel pipeline called State-Aware Tracker(SAT), which can produce accurate segmentation results with real-time speed. For higher efficiency, SAT takes advantage of the inter-frame consistency and deals with each target object as a tracklet. For more stable and robust performance over video sequences, SAT gets awareness for each state and makes self-adaptation via two feedback loops. One loop assists"},"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":"2003.00482","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-03-01T12:48:20Z","cross_cats_sorted":[],"title_canon_sha256":"30030b2ea164ff59b7f28b524bec9afe0d05864a62ff1e69553f6adbbae88028","abstract_canon_sha256":"1b5fff7aae5b86d8577349418017fe8e269b3fc9328fd0f164224ea6021fad84"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:44:47.646302Z","signature_b64":"6e1zytE2n68J39fPqQF+cnCWKvhkMvhdC+5KifGy1AaMlcfZsUhBkcwA6BotiG2H6cAwxMvpdPL4JP0yutJQAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9bfd848e2a22b8cfbd6b4cde1d4ba09150b37bb9f030109675de7a7411b976d","last_reissued_at":"2026-07-05T00:44:47.645936Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:44:47.645936Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"State-Aware Tracker for Real-Time Video Object Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Donglian Qi, Gang Yu, Jianxin Shen, Xi Chen, Ye Yuan, Zuoxin Li","submitted_at":"2020-03-01T12:48:20Z","abstract_excerpt":"In this work, we address the task of semi-supervised video object segmentation(VOS) and explore how to make efficient use of video property to tackle the challenge of semi-supervision. We propose a novel pipeline called State-Aware Tracker(SAT), which can produce accurate segmentation results with real-time speed. For higher efficiency, SAT takes advantage of the inter-frame consistency and deals with each target object as a tracklet. For more stable and robust performance over video sequences, SAT gets awareness for each state and makes self-adaptation via two feedback loops. One loop assists"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.00482","kind":"arxiv","version":1},"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/2003.00482/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":"2003.00482","created_at":"2026-07-05T00:44:47.645999+00:00"},{"alias_kind":"arxiv_version","alias_value":"2003.00482v1","created_at":"2026-07-05T00:44:47.645999+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.00482","created_at":"2026-07-05T00:44:47.645999+00:00"},{"alias_kind":"pith_short_12","alias_value":"XG75QSHCUIVY","created_at":"2026-07-05T00:44:47.645999+00:00"},{"alias_kind":"pith_short_16","alias_value":"XG75QSHCUIVYZ66W","created_at":"2026-07-05T00:44:47.645999+00:00"},{"alias_kind":"pith_short_8","alias_value":"XG75QSHC","created_at":"2026-07-05T00:44:47.645999+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/XG75QSHCUIVYZ66WWTG6DVF2BE","json":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE.json","graph_json":"https://pith.science/api/pith-number/XG75QSHCUIVYZ66WWTG6DVF2BE/graph.json","events_json":"https://pith.science/api/pith-number/XG75QSHCUIVYZ66WWTG6DVF2BE/events.json","paper":"https://pith.science/paper/XG75QSHC"},"agent_actions":{"view_html":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE","download_json":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE.json","view_paper":"https://pith.science/paper/XG75QSHC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2003.00482&json=true","fetch_graph":"https://pith.science/api/pith-number/XG75QSHCUIVYZ66WWTG6DVF2BE/graph.json","fetch_events":"https://pith.science/api/pith-number/XG75QSHCUIVYZ66WWTG6DVF2BE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE/action/storage_attestation","attest_author":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE/action/author_attestation","sign_citation":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE/action/citation_signature","submit_replication":"https://pith.science/pith/XG75QSHCUIVYZ66WWTG6DVF2BE/action/replication_record"}},"created_at":"2026-07-05T00:44:47.645999+00:00","updated_at":"2026-07-05T00:44:47.645999+00:00"}