{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AOXVTEHM3ZJOS5MQE7MWCIZYZ2","short_pith_number":"pith:AOXVTEHM","canonical_record":{"source":{"id":"2408.03265","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-08-06T15:54:55Z","cross_cats_sorted":[],"title_canon_sha256":"5505c77d810dc43fd672af087aa557fddc3d3ce369b814a99355023c4f1355e8","abstract_canon_sha256":"358f59f525121203d86b4c37ba28aeada3380b49becf1778f46cb00f55c1bbc3"},"schema_version":"1.0"},"canonical_sha256":"03af5990ecde52e9759027d9612338ce8a3df5edb5d6b5cc0c84071f202586a2","source":{"kind":"arxiv","id":"2408.03265","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03265","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03265v3","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03265","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"AOXVTEHM3ZJO","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"AOXVTEHM3ZJOS5MQ","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"AOXVTEHM","created_at":"2026-07-05T11:18:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AOXVTEHM3ZJOS5MQE7MWCIZYZ2","target":"record","payload":{"canonical_record":{"source":{"id":"2408.03265","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-08-06T15:54:55Z","cross_cats_sorted":[],"title_canon_sha256":"5505c77d810dc43fd672af087aa557fddc3d3ce369b814a99355023c4f1355e8","abstract_canon_sha256":"358f59f525121203d86b4c37ba28aeada3380b49becf1778f46cb00f55c1bbc3"},"schema_version":"1.0"},"canonical_sha256":"03af5990ecde52e9759027d9612338ce8a3df5edb5d6b5cc0c84071f202586a2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:18:13.701118Z","signature_b64":"Euiv0YER6IyO80nTRGU0reB+CAI++8ojdX22pOD8F7ss/Nx5XiTBHNbvJ0L+x3aFORCc3xHKg3VoaAFkTJ/RAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"03af5990ecde52e9759027d9612338ce8a3df5edb5d6b5cc0c84071f202586a2","last_reissued_at":"2026-07-05T11:18:13.700635Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:18:13.700635Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.03265","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mkbwTWpBJH7KmIp0hguLOVNSB6pDLdB6Kp0HdsIKRC87cf59S0NulNkmWqPUE0xLOPEtFP+0qywrAfIi95mnBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T21:37:47.391747Z"},"content_sha256":"e9ce86b48a124f5c2c67846ecaf86e562b0e47c3cc65854fb32d14bd5a9bcf09","schema_version":"1.0","event_id":"sha256:e9ce86b48a124f5c2c67846ecaf86e562b0e47c3cc65854fb32d14bd5a9bcf09"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AOXVTEHM3ZJOS5MQE7MWCIZYZ2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BVI-AOM: A New Training Dataset for Deep Video Compression Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"David Bull, Fan Zhang, Jakub Nawa{\\l}a, Joel Sole, Xiaoqing Zhu, Yuxuan Jiang","submitted_at":"2024-08-06T15:54:55Z","abstract_excerpt":"Deep learning is now playing an important role in enhancing the performance of conventional hybrid video codecs. These learning-based methods typically require diverse and representative training material for optimization in order to achieve model generalization and optimal coding performance. However, existing datasets either offer limited content variability or come with restricted licensing terms constraining their use to research purposes only. To address these issues, we propose a new training dataset, named BVI-AOM, which contains 956 uncompressed sequences at various resolutions from 27"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03265","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/2408.03265/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DX2HV7qLtCwqgeOW0wYhqPWHQ3XuazXhK4VoBALesRulngOeQm9Qqx5nY2ejUi10bTlJG4tdH+AUpd7TvBH2Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T21:37:47.392334Z"},"content_sha256":"4db8c5c4a012aa81767d9217641c63dd04cb80b327b030c436bde1503601605c","schema_version":"1.0","event_id":"sha256:4db8c5c4a012aa81767d9217641c63dd04cb80b327b030c436bde1503601605c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/bundle.json","state_url":"https://pith.science/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/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":"2026-08-13T21:37:47Z","links":{"resolver":"https://pith.science/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2","bundle":"https://pith.science/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/bundle.json","state":"https://pith.science/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AOXVTEHM3ZJOS5MQE7MWCIZYZ2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AOXVTEHM3ZJOS5MQE7MWCIZYZ2","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":"358f59f525121203d86b4c37ba28aeada3380b49becf1778f46cb00f55c1bbc3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-08-06T15:54:55Z","title_canon_sha256":"5505c77d810dc43fd672af087aa557fddc3d3ce369b814a99355023c4f1355e8"},"schema_version":"1.0","source":{"id":"2408.03265","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.03265","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2408.03265v3","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.03265","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"AOXVTEHM3ZJO","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"AOXVTEHM3ZJOS5MQ","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"AOXVTEHM","created_at":"2026-07-05T11:18:13Z"}],"graph_snapshots":[{"event_id":"sha256:4db8c5c4a012aa81767d9217641c63dd04cb80b327b030c436bde1503601605c","target":"graph","created_at":"2026-07-05T11:18:13Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2408.03265/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning is now playing an important role in enhancing the performance of conventional hybrid video codecs. These learning-based methods typically require diverse and representative training material for optimization in order to achieve model generalization and optimal coding performance. However, existing datasets either offer limited content variability or come with restricted licensing terms constraining their use to research purposes only. To address these issues, we propose a new training dataset, named BVI-AOM, which contains 956 uncompressed sequences at various resolutions from 27","authors_text":"David Bull, Fan Zhang, Jakub Nawa{\\l}a, Joel Sole, Xiaoqing Zhu, Yuxuan Jiang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-08-06T15:54:55Z","title":"BVI-AOM: A New Training Dataset for Deep Video Compression Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.03265","kind":"arxiv","version":3},"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:e9ce86b48a124f5c2c67846ecaf86e562b0e47c3cc65854fb32d14bd5a9bcf09","target":"record","created_at":"2026-07-05T11:18:13Z","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":"358f59f525121203d86b4c37ba28aeada3380b49becf1778f46cb00f55c1bbc3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-08-06T15:54:55Z","title_canon_sha256":"5505c77d810dc43fd672af087aa557fddc3d3ce369b814a99355023c4f1355e8"},"schema_version":"1.0","source":{"id":"2408.03265","kind":"arxiv","version":3}},"canonical_sha256":"03af5990ecde52e9759027d9612338ce8a3df5edb5d6b5cc0c84071f202586a2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03af5990ecde52e9759027d9612338ce8a3df5edb5d6b5cc0c84071f202586a2","first_computed_at":"2026-07-05T11:18:13.700635Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:13.700635Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Euiv0YER6IyO80nTRGU0reB+CAI++8ojdX22pOD8F7ss/Nx5XiTBHNbvJ0L+x3aFORCc3xHKg3VoaAFkTJ/RAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:13.701118Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.03265","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9ce86b48a124f5c2c67846ecaf86e562b0e47c3cc65854fb32d14bd5a9bcf09","sha256:4db8c5c4a012aa81767d9217641c63dd04cb80b327b030c436bde1503601605c"],"state_sha256":"4fb8c9d4d56a0361819e0d3f4217416127c0dfeeb402a00273a9c9a19708b9fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mbHEiPFkrLBFg6AWpAtQ8EUZahoWPyPkznSmL65l7KeYkXEjv0TXWVJDNu4qYcgVW04ZiWFfQ6QRDBOCRSrsDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T21:37:47.418288Z","bundle_sha256":"32ccc58a1777cffc8568bc578693ba1f064ae2bc36ddb7723e33d975d86f0e92"}}