{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:3UZZEPRUYZW5WNHQOSM337ENQT","short_pith_number":"pith:3UZZEPRU","schema_version":"1.0","canonical_sha256":"dd33923e34c66ddb34f07499bdfc8d84cc2a66b8e611cb889d9cb52db5f6282a","source":{"kind":"arxiv","id":"2112.09908","version":1},"attestation_state":"computed","paper":{"title":"Anomaly Discovery in Semantic Segmentation via Distillation Comparison Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huan Zhou, Ronghua Liu, Shi Gong, Xiang Bai, Yu Zhou, Zengqiang Zheng","submitted_at":"2021-12-18T11:32:47Z","abstract_excerpt":"This paper aims to address the problem of anomaly discovery in semantic segmentation. Our key observation is that semantic classification plays a critical role in existing approaches, while the incorrectly classified pixels are easily regarded as anomalies. Such a phenomenon frequently appears and is rarely discussed, which significantly reduces the performance of anomaly discovery. To this end, we propose a novel Distillation Comparison Network (DiCNet). It comprises of a teacher branch which is a semantic segmentation network that removed the semantic classification head, and a student branc"},"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":"2112.09908","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-12-18T11:32:47Z","cross_cats_sorted":[],"title_canon_sha256":"e7546a9849586e2d7a1a424b8ab16c632311881d7b71a101dd1835682e36a362","abstract_canon_sha256":"bf7fae98c7bfdc623c14aea4bd76c6e37d40e53e38b1187352f48970e91bf61d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:42:08.374189Z","signature_b64":"OtyGx3bjLEPEbqQ2CZphl39GeQpsdB8c5Q9eqouvRZmm+rtVsTkCQpkxYshngS6f1d68msb+4SGAXO0pQ3qOCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd33923e34c66ddb34f07499bdfc8d84cc2a66b8e611cb889d9cb52db5f6282a","last_reissued_at":"2026-07-05T03:42:08.373774Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:42:08.373774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Anomaly Discovery in Semantic Segmentation via Distillation Comparison Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huan Zhou, Ronghua Liu, Shi Gong, Xiang Bai, Yu Zhou, Zengqiang Zheng","submitted_at":"2021-12-18T11:32:47Z","abstract_excerpt":"This paper aims to address the problem of anomaly discovery in semantic segmentation. Our key observation is that semantic classification plays a critical role in existing approaches, while the incorrectly classified pixels are easily regarded as anomalies. Such a phenomenon frequently appears and is rarely discussed, which significantly reduces the performance of anomaly discovery. To this end, we propose a novel Distillation Comparison Network (DiCNet). It comprises of a teacher branch which is a semantic segmentation network that removed the semantic classification head, and a student branc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.09908","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/2112.09908/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":"2112.09908","created_at":"2026-07-05T03:42:08.373842+00:00"},{"alias_kind":"arxiv_version","alias_value":"2112.09908v1","created_at":"2026-07-05T03:42:08.373842+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.09908","created_at":"2026-07-05T03:42:08.373842+00:00"},{"alias_kind":"pith_short_12","alias_value":"3UZZEPRUYZW5","created_at":"2026-07-05T03:42:08.373842+00:00"},{"alias_kind":"pith_short_16","alias_value":"3UZZEPRUYZW5WNHQ","created_at":"2026-07-05T03:42:08.373842+00:00"},{"alias_kind":"pith_short_8","alias_value":"3UZZEPRU","created_at":"2026-07-05T03:42:08.373842+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/3UZZEPRUYZW5WNHQOSM337ENQT","json":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT.json","graph_json":"https://pith.science/api/pith-number/3UZZEPRUYZW5WNHQOSM337ENQT/graph.json","events_json":"https://pith.science/api/pith-number/3UZZEPRUYZW5WNHQOSM337ENQT/events.json","paper":"https://pith.science/paper/3UZZEPRU"},"agent_actions":{"view_html":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT","download_json":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT.json","view_paper":"https://pith.science/paper/3UZZEPRU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2112.09908&json=true","fetch_graph":"https://pith.science/api/pith-number/3UZZEPRUYZW5WNHQOSM337ENQT/graph.json","fetch_events":"https://pith.science/api/pith-number/3UZZEPRUYZW5WNHQOSM337ENQT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT/action/storage_attestation","attest_author":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT/action/author_attestation","sign_citation":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT/action/citation_signature","submit_replication":"https://pith.science/pith/3UZZEPRUYZW5WNHQOSM337ENQT/action/replication_record"}},"created_at":"2026-07-05T03:42:08.373842+00:00","updated_at":"2026-07-05T03:42:08.373842+00:00"}