{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ILT6DLCD774O6LK6F6HQD5E5LZ","short_pith_number":"pith:ILT6DLCD","canonical_record":{"source":{"id":"2308.14105","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-27T13:22:55Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d1d597a43e3195fb6de50c52f8b9e0f3b9bcb47b7fa85818f1dc86baa4f11609","abstract_canon_sha256":"e698133f07bc1676c3e555b0749092bb12c1ea5562c9c8f81355fbbbbd75bf72"},"schema_version":"1.0"},"canonical_sha256":"42e7e1ac43fff8ef2d5e2f8f01f49d5e7c15d827fe313495eecfd2320ccc7bee","source":{"kind":"arxiv","id":"2308.14105","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.14105","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"arxiv_version","alias_value":"2308.14105v3","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.14105","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_12","alias_value":"ILT6DLCD774O","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_16","alias_value":"ILT6DLCD774O6LK6","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_8","alias_value":"ILT6DLCD","created_at":"2026-07-05T08:35:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ILT6DLCD774O6LK6F6HQD5E5LZ","target":"record","payload":{"canonical_record":{"source":{"id":"2308.14105","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-27T13:22:55Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d1d597a43e3195fb6de50c52f8b9e0f3b9bcb47b7fa85818f1dc86baa4f11609","abstract_canon_sha256":"e698133f07bc1676c3e555b0749092bb12c1ea5562c9c8f81355fbbbbd75bf72"},"schema_version":"1.0"},"canonical_sha256":"42e7e1ac43fff8ef2d5e2f8f01f49d5e7c15d827fe313495eecfd2320ccc7bee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:35:17.889893Z","signature_b64":"OrR2uWFQLHbqVWnVAnAHGngzdncm90AWtUCf7A5pj2vFgnCv0tTXMoWBuuum5AO2OakrNgSaPWr50DSCD8ZQBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"42e7e1ac43fff8ef2d5e2f8f01f49d5e7c15d827fe313495eecfd2320ccc7bee","last_reissued_at":"2026-07-05T08:35:17.889154Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:35:17.889154Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.14105","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":"2026-07-05T08:35:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AXpDDRYJSig4I1cNbjcEzDDiAc+f626HcODN4kDrKkmI3lyuYtMU21B31jJJOWK4+byp866BvNkKtz6LbVROBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:09:21.909708Z"},"content_sha256":"85810d1fcb302e3d6dabd4fe4ed408b83ca17b7f3fca878499839576d5cd0657","schema_version":"1.0","event_id":"sha256:85810d1fcb302e3d6dabd4fe4ed408b83ca17b7f3fca878499839576d5cd0657"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ILT6DLCD774O6LK6F6HQD5E5LZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unified and Dynamic Graph for Temporal Character Grouping in Long Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bei Gan, Hanjun Li, Liangsheng Xu, Ruizhi Qiao, Taian Guo, Wei Wen, Xiao Wang, Xing Sun, Xiujun Shu","submitted_at":"2023-08-27T13:22:55Z","abstract_excerpt":"Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervised clustering to graph-based supervised clustering. However, graph methods are built upon the premise of fixed affinity graphs, bringing many inexact connections. Besides, they extract multi-modal features with kinds of models, which are unfriendly to deployment. In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping. This is accomplished firstly by a unified represent"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.14105","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/2308.14105/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":"2026-07-05T08:35:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qJWa+fQSCthgys+fNfAx2oxQhOkg8UI/FqLBO+EVbYAZgWy0GqF12Gw3xfD21oYD4oLfCwXEJ17X++O7qUcRAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:09:21.910207Z"},"content_sha256":"c9417131aa213e5d4e0e0826bda099b83df079f014b175c2ba5e4173363f2d87","schema_version":"1.0","event_id":"sha256:c9417131aa213e5d4e0e0826bda099b83df079f014b175c2ba5e4173363f2d87"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/bundle.json","state_url":"https://pith.science/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/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":"2026-08-03T17:09:21Z","links":{"resolver":"https://pith.science/pith/ILT6DLCD774O6LK6F6HQD5E5LZ","bundle":"https://pith.science/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/bundle.json","state":"https://pith.science/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ILT6DLCD774O6LK6F6HQD5E5LZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ILT6DLCD774O6LK6F6HQD5E5LZ","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":"e698133f07bc1676c3e555b0749092bb12c1ea5562c9c8f81355fbbbbd75bf72","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-27T13:22:55Z","title_canon_sha256":"d1d597a43e3195fb6de50c52f8b9e0f3b9bcb47b7fa85818f1dc86baa4f11609"},"schema_version":"1.0","source":{"id":"2308.14105","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.14105","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"arxiv_version","alias_value":"2308.14105v3","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.14105","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_12","alias_value":"ILT6DLCD774O","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_16","alias_value":"ILT6DLCD774O6LK6","created_at":"2026-07-05T08:35:17Z"},{"alias_kind":"pith_short_8","alias_value":"ILT6DLCD","created_at":"2026-07-05T08:35:17Z"}],"graph_snapshots":[{"event_id":"sha256:c9417131aa213e5d4e0e0826bda099b83df079f014b175c2ba5e4173363f2d87","target":"graph","created_at":"2026-07-05T08:35:17Z","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/2308.14105/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Video temporal character grouping locates appearing moments of major characters within a video according to their identities. To this end, recent works have evolved from unsupervised clustering to graph-based supervised clustering. However, graph methods are built upon the premise of fixed affinity graphs, bringing many inexact connections. Besides, they extract multi-modal features with kinds of models, which are unfriendly to deployment. In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping. This is accomplished firstly by a unified represent","authors_text":"Bei Gan, Hanjun Li, Liangsheng Xu, Ruizhi Qiao, Taian Guo, Wei Wen, Xiao Wang, Xing Sun, Xiujun Shu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-27T13:22:55Z","title":"Unified and Dynamic Graph for Temporal Character Grouping in Long Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.14105","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":"sha256:85810d1fcb302e3d6dabd4fe4ed408b83ca17b7f3fca878499839576d5cd0657","target":"record","created_at":"2026-07-05T08:35:17Z","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":"e698133f07bc1676c3e555b0749092bb12c1ea5562c9c8f81355fbbbbd75bf72","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-27T13:22:55Z","title_canon_sha256":"d1d597a43e3195fb6de50c52f8b9e0f3b9bcb47b7fa85818f1dc86baa4f11609"},"schema_version":"1.0","source":{"id":"2308.14105","kind":"arxiv","version":3}},"canonical_sha256":"42e7e1ac43fff8ef2d5e2f8f01f49d5e7c15d827fe313495eecfd2320ccc7bee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"42e7e1ac43fff8ef2d5e2f8f01f49d5e7c15d827fe313495eecfd2320ccc7bee","first_computed_at":"2026-07-05T08:35:17.889154Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:17.889154Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OrR2uWFQLHbqVWnVAnAHGngzdncm90AWtUCf7A5pj2vFgnCv0tTXMoWBuuum5AO2OakrNgSaPWr50DSCD8ZQBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:17.889893Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.14105","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:85810d1fcb302e3d6dabd4fe4ed408b83ca17b7f3fca878499839576d5cd0657","sha256:c9417131aa213e5d4e0e0826bda099b83df079f014b175c2ba5e4173363f2d87"],"state_sha256":"38b6193c6cce67c23a4d7ed5fb456c74faef91f6e9f9b0c7fd9cd9d6cebe72de"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+J+h/OvmiSfJfkeTNl1h37MKp8xJ2grjITpYwNv4HNf+gOOkG8rJenS6lGF6lylB/1mXFy6Aik0+LM6/fekADQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:09:21.913541Z","bundle_sha256":"95f3dd89beba174b2f7db918002d20dd9a522d6a7860a24d2999323bdd0e3123"}}