{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:E7O4472NPEUH2JFRA7YKXMTOBT","short_pith_number":"pith:E7O4472N","schema_version":"1.0","canonical_sha256":"27ddce7f4d79287d24b107f0abb26e0cc606251805287dd32cb84eeeebf5194c","source":{"kind":"arxiv","id":"1705.08182","version":3},"attestation_state":"computed","paper":{"title":"Unmasking the abnormal events in video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bogdan Alexe, Marius Popescu, Radu Tudor Ionescu, Sorina Smeureanu","submitted_at":"2017-05-23T11:14:17Z","abstract_excerpt":"We propose a novel framework for abnormal event detection in video that requires no training sequences. Our framework is based on unmasking, a technique previously used for authorship verification in text documents, which we adapt to our task. We iteratively train a binary classifier to distinguish between two consecutive video sequences while removing at each step the most discriminant features. Higher training accuracy rates of the intermediately obtained classifiers represent abnormal events. To the best of our knowledge, this is the first work to apply unmasking for a computer vision task."},"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":"1705.08182","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-05-23T11:14:17Z","cross_cats_sorted":[],"title_canon_sha256":"70e40e833641e0221c19bfe9af87685aaede963c389081022f41bff73f3fea72","abstract_canon_sha256":"ee4428b8b2f93b76ea6b53cf4bd28202206b5fe976cf93c06be4529e2f1b789e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:34.842488Z","signature_b64":"fBGk89v2qyIasPWByG8M6/Kw7TmltWKx0gaZOa00GLXj3IBqSqUrvW3kylzdS9XoDELnZPQ5wa4KYU9+/bGFDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27ddce7f4d79287d24b107f0abb26e0cc606251805287dd32cb84eeeebf5194c","last_reissued_at":"2026-05-18T00:39:34.841820Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:34.841820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unmasking the abnormal events in video","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bogdan Alexe, Marius Popescu, Radu Tudor Ionescu, Sorina Smeureanu","submitted_at":"2017-05-23T11:14:17Z","abstract_excerpt":"We propose a novel framework for abnormal event detection in video that requires no training sequences. Our framework is based on unmasking, a technique previously used for authorship verification in text documents, which we adapt to our task. We iteratively train a binary classifier to distinguish between two consecutive video sequences while removing at each step the most discriminant features. Higher training accuracy rates of the intermediately obtained classifiers represent abnormal events. To the best of our knowledge, this is the first work to apply unmasking for a computer vision task."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.08182","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":""},"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":"1705.08182","created_at":"2026-05-18T00:39:34.841926+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.08182v3","created_at":"2026-05-18T00:39:34.841926+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.08182","created_at":"2026-05-18T00:39:34.841926+00:00"},{"alias_kind":"pith_short_12","alias_value":"E7O4472NPEUH","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_16","alias_value":"E7O4472NPEUH2JFR","created_at":"2026-05-18T12:31:12.930513+00:00"},{"alias_kind":"pith_short_8","alias_value":"E7O4472N","created_at":"2026-05-18T12:31:12.930513+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/E7O4472NPEUH2JFRA7YKXMTOBT","json":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT.json","graph_json":"https://pith.science/api/pith-number/E7O4472NPEUH2JFRA7YKXMTOBT/graph.json","events_json":"https://pith.science/api/pith-number/E7O4472NPEUH2JFRA7YKXMTOBT/events.json","paper":"https://pith.science/paper/E7O4472N"},"agent_actions":{"view_html":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT","download_json":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT.json","view_paper":"https://pith.science/paper/E7O4472N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.08182&json=true","fetch_graph":"https://pith.science/api/pith-number/E7O4472NPEUH2JFRA7YKXMTOBT/graph.json","fetch_events":"https://pith.science/api/pith-number/E7O4472NPEUH2JFRA7YKXMTOBT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT/action/storage_attestation","attest_author":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT/action/author_attestation","sign_citation":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT/action/citation_signature","submit_replication":"https://pith.science/pith/E7O4472NPEUH2JFRA7YKXMTOBT/action/replication_record"}},"created_at":"2026-05-18T00:39:34.841926+00:00","updated_at":"2026-05-18T00:39:34.841926+00:00"}