{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:EEO35BQLMWU3I72D6MFJ4GA5FG","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":"aabddf84883c87659856c3c598b97435464ac2b2f42b8e2ccbd43c6df9541032","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T01:59:43Z","title_canon_sha256":"5f8fa250f3b1a904989deedb4a663b24e38654379ed432670523afff0d4e5d52"},"schema_version":"1.0","source":{"id":"2403.13238","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13238","created_at":"2026-07-05T11:21:31Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13238v3","created_at":"2026-07-05T11:21:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13238","created_at":"2026-07-05T11:21:31Z"},{"alias_kind":"pith_short_12","alias_value":"EEO35BQLMWU3","created_at":"2026-07-05T11:21:31Z"},{"alias_kind":"pith_short_16","alias_value":"EEO35BQLMWU3I72D","created_at":"2026-07-05T11:21:31Z"},{"alias_kind":"pith_short_8","alias_value":"EEO35BQL","created_at":"2026-07-05T11:21:31Z"}],"graph_snapshots":[{"event_id":"sha256:4e6f4dabf7ab50fa381849aa1fe7b4461826a105fc4c08e82f55c5fac3eb91ac","target":"graph","created_at":"2026-07-05T11:21:31Z","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/2403.13238/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Directly learning to model 4D content, including shape, color, and motion, is challenging. Existing methods rely on pose priors for motion control, resulting in limited motion diversity and continuity in details. To address this, we propose a framework that generates volumetric 4D sequences, where 3D shapes are animated under given conditions (text-image guidance) with dynamic evolution in shape and color across spatial and temporal dimensions, allowing for free navigation and rendering from any direction. We first use a coherent 3D shape and color modeling to encode the shape and color of eac","authors_text":"Ajmal Mian, Mingtao Feng, Qitong Yang, Shijie Sun, Weisheng Dong, Yaonan Wang, Zijie Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T01:59:43Z","title":"Learning Coherent Matrixized Representation in Latent Space for Volumetric 4D Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13238","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:a0730cf93df88f69b5b182baef7660b2de2117c306add1611b3145a499973f82","target":"record","created_at":"2026-07-05T11:21:31Z","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":"aabddf84883c87659856c3c598b97435464ac2b2f42b8e2ccbd43c6df9541032","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T01:59:43Z","title_canon_sha256":"5f8fa250f3b1a904989deedb4a663b24e38654379ed432670523afff0d4e5d52"},"schema_version":"1.0","source":{"id":"2403.13238","kind":"arxiv","version":3}},"canonical_sha256":"211dbe860b65a9b47f43f30a9e181d298aae4cdb82d628d57f5312c480291aaf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"211dbe860b65a9b47f43f30a9e181d298aae4cdb82d628d57f5312c480291aaf","first_computed_at":"2026-07-05T11:21:31.817803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:31.817803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RQYge0WMf7JsvO9POvMbREKXhIC9KUqtnlK9CqHBdI6DqA6oec24Uk+/afpxQDNNgH0Gqd/U97sOXtKm/yvIBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:31.818275Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.13238","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0730cf93df88f69b5b182baef7660b2de2117c306add1611b3145a499973f82","sha256:4e6f4dabf7ab50fa381849aa1fe7b4461826a105fc4c08e82f55c5fac3eb91ac"],"state_sha256":"c0c8a8d94b3d86c9b5d578e9ae7a361303ee6bbb52ba880d6b954a0527fb8735"}