{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3IUKMGOZ3PDZIR3ULUVYJFST2P","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":"fc063913cc41b0f9a8b26072fd53cbf3bf33e97f6bd6da7451a8eb3ea0566451","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-22T09:49:48Z","title_canon_sha256":"5bfb1dde6d3552aaf1ff4942c448e6420f96cb4423fa92bd448bb96d8ba6d9c4"},"schema_version":"1.0","source":{"id":"2412.16948","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16948","created_at":"2026-07-05T09:53:15Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16948v1","created_at":"2026-07-05T09:53:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16948","created_at":"2026-07-05T09:53:15Z"},{"alias_kind":"pith_short_12","alias_value":"3IUKMGOZ3PDZ","created_at":"2026-07-05T09:53:15Z"},{"alias_kind":"pith_short_16","alias_value":"3IUKMGOZ3PDZIR3U","created_at":"2026-07-05T09:53:15Z"},{"alias_kind":"pith_short_8","alias_value":"3IUKMGOZ","created_at":"2026-07-05T09:53:15Z"}],"graph_snapshots":[{"event_id":"sha256:9b58eb378e461bb6c5d201a7781d0b47fa6202a43ed973ca41be1bc66086857a","target":"graph","created_at":"2026-07-05T09:53:15Z","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/2412.16948/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dynamic texture synthesis aims to generate sequences that are visually similar to a reference video texture and exhibit specific stationary properties in time. In this paper, we introduce a spatiotemporal generative adversarial network (DTSGAN) that can learn from a single dynamic texture by capturing its motion and content distribution. With the pipeline of DTSGAN, a new video sequence is generated from the coarsest scale to the finest one. To avoid mode collapse, we propose a novel strategy for data updates that helps improve the diversity of generated results. Qualitative and quantitative e","authors_text":"Ao Xiang, Han Cao, Xiangtian Li, Xiaobo Wang, Zhaoyang Zhang, Zhen Qi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-22T09:49:48Z","title":"DTSGAN: Learning Dynamic Textures via Spatiotemporal Generative Adversarial Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16948","kind":"arxiv","version":1},"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":"sha256:1ae55350668f08befff14f861acf2db37db5c133f79bad3bd52e86c3c9f6cbbe","target":"record","created_at":"2026-07-05T09:53:15Z","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":"fc063913cc41b0f9a8b26072fd53cbf3bf33e97f6bd6da7451a8eb3ea0566451","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-22T09:49:48Z","title_canon_sha256":"5bfb1dde6d3552aaf1ff4942c448e6420f96cb4423fa92bd448bb96d8ba6d9c4"},"schema_version":"1.0","source":{"id":"2412.16948","kind":"arxiv","version":1}},"canonical_sha256":"da28a619d9dbc79447745d2b849653d3c599a89c2f8c793e9879a1736f7de933","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da28a619d9dbc79447745d2b849653d3c599a89c2f8c793e9879a1736f7de933","first_computed_at":"2026-07-05T09:53:15.325895Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:53:15.325895Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XevXxbzx7sWDm8s5obouSOGuraqQPpSxkBS3Fw+Qu073yKMMXlqQLvqX3Dqt0tES4a1ATNxemwaL/HCSQruuAg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:53:15.326396Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.16948","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ae55350668f08befff14f861acf2db37db5c133f79bad3bd52e86c3c9f6cbbe","sha256:9b58eb378e461bb6c5d201a7781d0b47fa6202a43ed973ca41be1bc66086857a"],"state_sha256":"74f40ae6db92e48a15707f40712297e7f24acc0bea0985ef12bd5e6219f2d6f9"}