{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:EQEJ3BLTHLDH75SDOVURMSHGWW","short_pith_number":"pith:EQEJ3BLT","canonical_record":{"source":{"id":"2309.07906","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-14T17:54:01Z","cross_cats_sorted":[],"title_canon_sha256":"d1ddb209e43836fe3202e845788cc954664c35e53c6783e9e4e0b12453cd9827","abstract_canon_sha256":"2cf93accf305193e07001bd76e537734243c5118596b1a942649208161e032e6"},"schema_version":"1.0"},"canonical_sha256":"24089d85733ac67ff64375691648e6b5a6c5652c11d0d6f170c037d402ff8cfa","source":{"kind":"arxiv","id":"2309.07906","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.07906","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"arxiv_version","alias_value":"2309.07906v3","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.07906","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_12","alias_value":"EQEJ3BLTHLDH","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_16","alias_value":"EQEJ3BLTHLDH75SD","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_8","alias_value":"EQEJ3BLT","created_at":"2026-07-05T08:19:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:EQEJ3BLTHLDH75SDOVURMSHGWW","target":"record","payload":{"canonical_record":{"source":{"id":"2309.07906","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-14T17:54:01Z","cross_cats_sorted":[],"title_canon_sha256":"d1ddb209e43836fe3202e845788cc954664c35e53c6783e9e4e0b12453cd9827","abstract_canon_sha256":"2cf93accf305193e07001bd76e537734243c5118596b1a942649208161e032e6"},"schema_version":"1.0"},"canonical_sha256":"24089d85733ac67ff64375691648e6b5a6c5652c11d0d6f170c037d402ff8cfa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:19:07.422604Z","signature_b64":"ciN6F/3icS4aaB2hkQ6bjPXn9DujSYpRqiE5eDnvHMgBF/W6PdQJSQxXtexWZ73raNcUKsjfX8Bbm0wsZFpMBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24089d85733ac67ff64375691648e6b5a6c5652c11d0d6f170c037d402ff8cfa","last_reissued_at":"2026-07-05T08:19:07.422118Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:19:07.422118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.07906","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":"2026-07-05T08:19:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FG7ZMADTSVhlucRAAeCDNHW46Ii52wq8qHBThqw8UoE/cm+GuKv1JzlgsU9ksP/E3b8oWIHFUuw7PRxMuij4Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:39:14.960463Z"},"content_sha256":"5727036226fd827e50ba284dc24c722defe98fef65e5b03b8aeb5929e973c780","schema_version":"1.0","event_id":"sha256:5727036226fd827e50ba284dc24c722defe98fef65e5b03b8aeb5929e973c780"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:EQEJ3BLTHLDH75SDOVURMSHGWW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generative Image Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aleksander Holynski, Noah Snavely, Richard Tucker, Zhengqi Li","submitted_at":"2023-09-14T17:54:01Z","abstract_excerpt":"We present an approach to modeling an image-space prior on scene motion. Our prior is learned from a collection of motion trajectories extracted from real video sequences depicting natural, oscillatory dynamics such as trees, flowers, candles, and clothes swaying in the wind. We model this dense, long-term motion prior in the Fourier domain:given a single image, our trained model uses a frequency-coordinated diffusion sampling process to predict a spectral volume, which can be converted into a motion texture that spans an entire video. Along with an image-based rendering module, these trajecto"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.07906","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/2309.07906/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":"2026-07-05T08:19:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"okXHTmDxSLx46jO7GpyxmqUyPP3DP8UWB+KF3Q9Z4+c2GxkudNdl3kjx7JJasMoUBzZxRnxy3M9rs/37LaKQDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:39:14.960854Z"},"content_sha256":"9348df75168f16ec945278574ae4b86e5b3214a003327347850e257c1134f65c","schema_version":"1.0","event_id":"sha256:9348df75168f16ec945278574ae4b86e5b3214a003327347850e257c1134f65c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/bundle.json","state_url":"https://pith.science/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/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":"2026-08-13T03:39:14Z","links":{"resolver":"https://pith.science/pith/EQEJ3BLTHLDH75SDOVURMSHGWW","bundle":"https://pith.science/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/bundle.json","state":"https://pith.science/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EQEJ3BLTHLDH75SDOVURMSHGWW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:EQEJ3BLTHLDH75SDOVURMSHGWW","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":"2cf93accf305193e07001bd76e537734243c5118596b1a942649208161e032e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-14T17:54:01Z","title_canon_sha256":"d1ddb209e43836fe3202e845788cc954664c35e53c6783e9e4e0b12453cd9827"},"schema_version":"1.0","source":{"id":"2309.07906","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.07906","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"arxiv_version","alias_value":"2309.07906v3","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.07906","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_12","alias_value":"EQEJ3BLTHLDH","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_16","alias_value":"EQEJ3BLTHLDH75SD","created_at":"2026-07-05T08:19:07Z"},{"alias_kind":"pith_short_8","alias_value":"EQEJ3BLT","created_at":"2026-07-05T08:19:07Z"}],"graph_snapshots":[{"event_id":"sha256:9348df75168f16ec945278574ae4b86e5b3214a003327347850e257c1134f65c","target":"graph","created_at":"2026-07-05T08:19:07Z","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/2309.07906/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present an approach to modeling an image-space prior on scene motion. Our prior is learned from a collection of motion trajectories extracted from real video sequences depicting natural, oscillatory dynamics such as trees, flowers, candles, and clothes swaying in the wind. We model this dense, long-term motion prior in the Fourier domain:given a single image, our trained model uses a frequency-coordinated diffusion sampling process to predict a spectral volume, which can be converted into a motion texture that spans an entire video. Along with an image-based rendering module, these trajecto","authors_text":"Aleksander Holynski, Noah Snavely, Richard Tucker, Zhengqi Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-14T17:54:01Z","title":"Generative Image Dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.07906","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":"sha256:5727036226fd827e50ba284dc24c722defe98fef65e5b03b8aeb5929e973c780","target":"record","created_at":"2026-07-05T08:19:07Z","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":"2cf93accf305193e07001bd76e537734243c5118596b1a942649208161e032e6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-14T17:54:01Z","title_canon_sha256":"d1ddb209e43836fe3202e845788cc954664c35e53c6783e9e4e0b12453cd9827"},"schema_version":"1.0","source":{"id":"2309.07906","kind":"arxiv","version":3}},"canonical_sha256":"24089d85733ac67ff64375691648e6b5a6c5652c11d0d6f170c037d402ff8cfa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24089d85733ac67ff64375691648e6b5a6c5652c11d0d6f170c037d402ff8cfa","first_computed_at":"2026-07-05T08:19:07.422118Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:19:07.422118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ciN6F/3icS4aaB2hkQ6bjPXn9DujSYpRqiE5eDnvHMgBF/W6PdQJSQxXtexWZ73raNcUKsjfX8Bbm0wsZFpMBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:19:07.422604Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.07906","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5727036226fd827e50ba284dc24c722defe98fef65e5b03b8aeb5929e973c780","sha256:9348df75168f16ec945278574ae4b86e5b3214a003327347850e257c1134f65c"],"state_sha256":"012a79c3dea4656165f265a94018b9205b5d79e1d606fccd22ef18b35a6344c7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r+KkZitZSEaT/hZEuPWP85VCraSYd9M18VlKhIQOfi3LlzoG73b5BWu5oITUi3WEXlgm0BlczcaEoXFSG3LOAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T03:39:14.963007Z","bundle_sha256":"195e8d9d6f8178a4eb5784222f889486bb30fd72a3384053ec5f3c6010bcf690"}}