{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:PVC5RJVZ4BMAQFQ6ZTIWOHEZXT","short_pith_number":"pith:PVC5RJVZ","schema_version":"1.0","canonical_sha256":"7d45d8a6b9e05808161eccd1671c99bcc25938172ff933cd133550cdacb68a49","source":{"kind":"arxiv","id":"2412.02479","version":2},"attestation_state":"computed","paper":{"title":"OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Caixin Kang, Jiayi Wang, Ruochen Zhang, Shan Fu, Shiji Zhao, Shouwei Ruan, Xingxing Wei, Yubo Chen","submitted_at":"2024-12-03T14:42:31Z","abstract_excerpt":"With the rise of deep learning, facial recognition technology has seen extensive research and rapid development. Although facial recognition is considered a mature technology, we find that existing open-source models and commercial algorithms lack robustness in certain complex Out-of-Distribution (OOD) scenarios, raising concerns about the reliability of these systems. In this paper, we introduce OODFace, which explores the OOD challenges faced by facial recognition models from two perspectives: common corruptions and appearance variations. We systematically design 30 OOD scenarios across 9 ma"},"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":"2412.02479","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-03T14:42:31Z","cross_cats_sorted":["cs.AI","cs.CR","cs.LG"],"title_canon_sha256":"e878d3ff1b69ef3086ca08cd3012af3e2344a5cee690762d89d1dcb7c224d777","abstract_canon_sha256":"c788a2049b897906172b56abd9042a501742fc6e4590bfadb8bec2d3fb6d4ca9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:40:14.848089Z","signature_b64":"EQ1352uOAI8XAU0Yv9raYzrkAg18g8R7uAcoygmGUrkE6gTB4gl/lNeBF80jX2frzdV0IOulzg+EWoPmFaOmAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7d45d8a6b9e05808161eccd1671c99bcc25938172ff933cd133550cdacb68a49","last_reissued_at":"2026-07-05T10:40:14.847624Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:40:14.847624Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"OODFace: Benchmarking Robustness of Face Recognition under Common Corruptions and Appearance Variations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Caixin Kang, Jiayi Wang, Ruochen Zhang, Shan Fu, Shiji Zhao, Shouwei Ruan, Xingxing Wei, Yubo Chen","submitted_at":"2024-12-03T14:42:31Z","abstract_excerpt":"With the rise of deep learning, facial recognition technology has seen extensive research and rapid development. Although facial recognition is considered a mature technology, we find that existing open-source models and commercial algorithms lack robustness in certain complex Out-of-Distribution (OOD) scenarios, raising concerns about the reliability of these systems. In this paper, we introduce OODFace, which explores the OOD challenges faced by facial recognition models from two perspectives: common corruptions and appearance variations. We systematically design 30 OOD scenarios across 9 ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.02479","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/2412.02479/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":"2412.02479","created_at":"2026-07-05T10:40:14.847682+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.02479v2","created_at":"2026-07-05T10:40:14.847682+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.02479","created_at":"2026-07-05T10:40:14.847682+00:00"},{"alias_kind":"pith_short_12","alias_value":"PVC5RJVZ4BMA","created_at":"2026-07-05T10:40:14.847682+00:00"},{"alias_kind":"pith_short_16","alias_value":"PVC5RJVZ4BMAQFQ6","created_at":"2026-07-05T10:40:14.847682+00:00"},{"alias_kind":"pith_short_8","alias_value":"PVC5RJVZ","created_at":"2026-07-05T10:40:14.847682+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/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT","json":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT.json","graph_json":"https://pith.science/api/pith-number/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/graph.json","events_json":"https://pith.science/api/pith-number/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/events.json","paper":"https://pith.science/paper/PVC5RJVZ"},"agent_actions":{"view_html":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT","download_json":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT.json","view_paper":"https://pith.science/paper/PVC5RJVZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.02479&json=true","fetch_graph":"https://pith.science/api/pith-number/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/graph.json","fetch_events":"https://pith.science/api/pith-number/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/action/storage_attestation","attest_author":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/action/author_attestation","sign_citation":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/action/citation_signature","submit_replication":"https://pith.science/pith/PVC5RJVZ4BMAQFQ6ZTIWOHEZXT/action/replication_record"}},"created_at":"2026-07-05T10:40:14.847682+00:00","updated_at":"2026-07-05T10:40:14.847682+00:00"}