{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:HTVFLCYUY43JKELK7IJXT3VPYN","short_pith_number":"pith:HTVFLCYU","schema_version":"1.0","canonical_sha256":"3cea558b14c73695116afa1379eeafc35ca7947d3ab8348ded4f6e9b9de1bcce","source":{"kind":"arxiv","id":"2304.13509","version":3},"attestation_state":"computed","paper":{"title":"EasyPortrait -- Face Parsing and Portrait Segmentation Dataset","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexander Kapitanov, Alexander Sautin, Elizaveta Petrova, Karen Efremyan, Karina Kvanchiani","submitted_at":"2023-04-26T12:51:34Z","abstract_excerpt":"Recently, video conferencing apps have become functional by accomplishing such computer vision-based features as real-time background removal and face beautification. Limited variability in existing portrait segmentation and face parsing datasets, including head poses, ethnicity, scenes, and occlusions specific to video conferencing, motivated us to create a new dataset, EasyPortrait, for these tasks simultaneously. It contains 40,000 primarily indoor photos repeating video meeting scenarios with 13,705 unique users and fine-grained segmentation masks separated into 9 classes. Inappropriate an"},"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":"2304.13509","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-26T12:51:34Z","cross_cats_sorted":[],"title_canon_sha256":"451e6d92d2d13432ccb854aaad0805b42042b25144da14875007e6896873c382","abstract_canon_sha256":"ddee719fb9c2d7c22c39bbf52d3190ca1e96c6ca6e867885f74557430e64e9c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:08.170864Z","signature_b64":"Kdzhv1iEOb/I3Q+ge/8UaHzxQgs7i43xnA88l0MijAo+U4jYV7a4fbf/86t8fBD8Q1OHqKG061h/JeAmAZ62Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3cea558b14c73695116afa1379eeafc35ca7947d3ab8348ded4f6e9b9de1bcce","last_reissued_at":"2026-07-05T07:53:08.170426Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:08.170426Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EasyPortrait -- Face Parsing and Portrait Segmentation Dataset","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexander Kapitanov, Alexander Sautin, Elizaveta Petrova, Karen Efremyan, Karina Kvanchiani","submitted_at":"2023-04-26T12:51:34Z","abstract_excerpt":"Recently, video conferencing apps have become functional by accomplishing such computer vision-based features as real-time background removal and face beautification. Limited variability in existing portrait segmentation and face parsing datasets, including head poses, ethnicity, scenes, and occlusions specific to video conferencing, motivated us to create a new dataset, EasyPortrait, for these tasks simultaneously. It contains 40,000 primarily indoor photos repeating video meeting scenarios with 13,705 unique users and fine-grained segmentation masks separated into 9 classes. Inappropriate an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.13509","kind":"arxiv","version":3},"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/2304.13509/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":"2304.13509","created_at":"2026-07-05T07:53:08.170483+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.13509v3","created_at":"2026-07-05T07:53:08.170483+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.13509","created_at":"2026-07-05T07:53:08.170483+00:00"},{"alias_kind":"pith_short_12","alias_value":"HTVFLCYUY43J","created_at":"2026-07-05T07:53:08.170483+00:00"},{"alias_kind":"pith_short_16","alias_value":"HTVFLCYUY43JKELK","created_at":"2026-07-05T07:53:08.170483+00:00"},{"alias_kind":"pith_short_8","alias_value":"HTVFLCYU","created_at":"2026-07-05T07:53:08.170483+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.25578","citing_title":"H-Adapter: Pose-Robust Hairstyle Transfer via Attention-Derived, Source-Aligned Hair Masks","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2604.20585","citing_title":"On the Impact of Face Segmentation-Based Background Removal on Recognition and Morphing Attack Detection","ref_index":28,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN","json":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN.json","graph_json":"https://pith.science/api/pith-number/HTVFLCYUY43JKELK7IJXT3VPYN/graph.json","events_json":"https://pith.science/api/pith-number/HTVFLCYUY43JKELK7IJXT3VPYN/events.json","paper":"https://pith.science/paper/HTVFLCYU"},"agent_actions":{"view_html":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN","download_json":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN.json","view_paper":"https://pith.science/paper/HTVFLCYU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.13509&json=true","fetch_graph":"https://pith.science/api/pith-number/HTVFLCYUY43JKELK7IJXT3VPYN/graph.json","fetch_events":"https://pith.science/api/pith-number/HTVFLCYUY43JKELK7IJXT3VPYN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN/action/storage_attestation","attest_author":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN/action/author_attestation","sign_citation":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN/action/citation_signature","submit_replication":"https://pith.science/pith/HTVFLCYUY43JKELK7IJXT3VPYN/action/replication_record"}},"created_at":"2026-07-05T07:53:08.170483+00:00","updated_at":"2026-07-05T07:53:08.170483+00:00"}