{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:FUJ3GYH7E4XHVOEKKRUV233T5B","short_pith_number":"pith:FUJ3GYH7","canonical_record":{"source":{"id":"1903.00618","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-02T03:24:21Z","cross_cats_sorted":[],"title_canon_sha256":"d1e400cbb1c4dce7cbd4733b41fe93882d1eb311ab6fa7d9ec42653c5b3858fb","abstract_canon_sha256":"32ebb44508ca676643973496872b0fca7f220d62e7f5ff1e3babe77751415c97"},"schema_version":"1.0"},"canonical_sha256":"2d13b360ff272e7ab88a54695d6f73e8421a40807434f401fe3768b014ae1a39","source":{"kind":"arxiv","id":"1903.00618","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00618","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00618v4","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00618","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"pith_short_12","alias_value":"FUJ3GYH7E4XH","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FUJ3GYH7E4XHVOEK","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FUJ3GYH7","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:FUJ3GYH7E4XHVOEKKRUV233T5B","target":"record","payload":{"canonical_record":{"source":{"id":"1903.00618","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-02T03:24:21Z","cross_cats_sorted":[],"title_canon_sha256":"d1e400cbb1c4dce7cbd4733b41fe93882d1eb311ab6fa7d9ec42653c5b3858fb","abstract_canon_sha256":"32ebb44508ca676643973496872b0fca7f220d62e7f5ff1e3babe77751415c97"},"schema_version":"1.0"},"canonical_sha256":"2d13b360ff272e7ab88a54695d6f73e8421a40807434f401fe3768b014ae1a39","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:30.442228Z","signature_b64":"auB9IUptg0uwz79KYj5BNCKifrwH2ekwGSz1yCdGF7KKXeuvtjgtyeywiJFFJwEv1g6DsM93SZZfHlomInkkAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d13b360ff272e7ab88a54695d6f73e8421a40807434f401fe3768b014ae1a39","last_reissued_at":"2026-05-17T23:39:30.441644Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:30.441644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.00618","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:39:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7RIQ2vynCgk9kXtzRX3ffrcuRcze5Jatg6IFo5l75UWR0vXvXSWyX0uZR1Yrpm2YxeNdNKJU6gtduYTF1a28Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T07:26:28.130281Z"},"content_sha256":"05dbf7a1c7439b4352bb2bf51ee336815232eca6a4e94859c44ba3417a6d2544","schema_version":"1.0","event_id":"sha256:05dbf7a1c7439b4352bb2bf51ee336815232eca6a4e94859c44ba3417a6d2544"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:FUJ3GYH7E4XHVOEKKRUV233T5B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised Traffic Accident Detection in First-Person Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"David J. Crandall, Ella M. Atkins, Mingze Xu, Yuchen Wang, Yu Yao","submitted_at":"2019-03-02T03:24:21Z","abstract_excerpt":"Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems. However, most work on video anomaly detection suffers from two crucial drawbacks. First, they assume cameras are fixed and videos have static backgrounds, which is reasonable for surveillance applications but not for vehicle-mounted cameras. Second, they pose the problem as one-class classification, relying on arduously hand-labeled training datasets that limit recognition to anomaly categories that have been expli"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00618","kind":"arxiv","version":4},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:39:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gl15oEFlw68azuTmOpH3/GVky9MJXvQI3dVu8+YRhU3x/vR7cArR50JKg7QKpNqGrgYLKYGO9JzqEVKDlwDWAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T07:26:28.130636Z"},"content_sha256":"ea03709faf062f5a4919d652bb0ed9b3159dbf4c52e63225a6e06dad29a141e2","schema_version":"1.0","event_id":"sha256:ea03709faf062f5a4919d652bb0ed9b3159dbf4c52e63225a6e06dad29a141e2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/bundle.json","state_url":"https://pith.science/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-27T07:26:28Z","links":{"resolver":"https://pith.science/pith/FUJ3GYH7E4XHVOEKKRUV233T5B","bundle":"https://pith.science/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/bundle.json","state":"https://pith.science/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FUJ3GYH7E4XHVOEKKRUV233T5B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FUJ3GYH7E4XHVOEKKRUV233T5B","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"32ebb44508ca676643973496872b0fca7f220d62e7f5ff1e3babe77751415c97","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-02T03:24:21Z","title_canon_sha256":"d1e400cbb1c4dce7cbd4733b41fe93882d1eb311ab6fa7d9ec42653c5b3858fb"},"schema_version":"1.0","source":{"id":"1903.00618","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00618","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00618v4","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00618","created_at":"2026-05-17T23:39:30Z"},{"alias_kind":"pith_short_12","alias_value":"FUJ3GYH7E4XH","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FUJ3GYH7E4XHVOEK","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FUJ3GYH7","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:ea03709faf062f5a4919d652bb0ed9b3159dbf4c52e63225a6e06dad29a141e2","target":"graph","created_at":"2026-05-17T23:39:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Recognizing abnormal events such as traffic violations and accidents in natural driving scenes is essential for successful autonomous driving and advanced driver assistance systems. However, most work on video anomaly detection suffers from two crucial drawbacks. First, they assume cameras are fixed and videos have static backgrounds, which is reasonable for surveillance applications but not for vehicle-mounted cameras. Second, they pose the problem as one-class classification, relying on arduously hand-labeled training datasets that limit recognition to anomaly categories that have been expli","authors_text":"David J. Crandall, Ella M. Atkins, Mingze Xu, Yuchen Wang, Yu Yao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-02T03:24:21Z","title":"Unsupervised Traffic Accident Detection in First-Person Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00618","kind":"arxiv","version":4},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:05dbf7a1c7439b4352bb2bf51ee336815232eca6a4e94859c44ba3417a6d2544","target":"record","created_at":"2026-05-17T23:39:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"32ebb44508ca676643973496872b0fca7f220d62e7f5ff1e3babe77751415c97","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-02T03:24:21Z","title_canon_sha256":"d1e400cbb1c4dce7cbd4733b41fe93882d1eb311ab6fa7d9ec42653c5b3858fb"},"schema_version":"1.0","source":{"id":"1903.00618","kind":"arxiv","version":4}},"canonical_sha256":"2d13b360ff272e7ab88a54695d6f73e8421a40807434f401fe3768b014ae1a39","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d13b360ff272e7ab88a54695d6f73e8421a40807434f401fe3768b014ae1a39","first_computed_at":"2026-05-17T23:39:30.441644Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:30.441644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"auB9IUptg0uwz79KYj5BNCKifrwH2ekwGSz1yCdGF7KKXeuvtjgtyeywiJFFJwEv1g6DsM93SZZfHlomInkkAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:30.442228Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.00618","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:05dbf7a1c7439b4352bb2bf51ee336815232eca6a4e94859c44ba3417a6d2544","sha256:ea03709faf062f5a4919d652bb0ed9b3159dbf4c52e63225a6e06dad29a141e2"],"state_sha256":"93b0c7d3bc92c54b5005b739bc2ac055089692e46435d6b505f0c1b89f890c62"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bfN0JwVde4F/EKwLt0jroh59GSdU8i5+AsPsejKsISEmJkdNZip0WsiirZUQd6vNcDnlEe6/ELONeZtBCOHXBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T07:26:28.132594Z","bundle_sha256":"a144dd9402096d101a5cc08cef7ced187912a20c75f441f3bd9a606c6ee03ac8"}}