{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:POGL2JWUZKIOO3AIM6IU3B3JCT","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":"18814fa6bfa4801d72930f2c0ae1a7e66b67c4b111b1cecde44158eda51b4b6a","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T08:13:38Z","title_canon_sha256":"7fa6eb64c5ec6386439864b007b2d9c21e3c7aea24f3064e5fce9a560a251a8b"},"schema_version":"1.0","source":{"id":"2412.06285","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.06285","created_at":"2026-07-05T09:46:18Z"},{"alias_kind":"arxiv_version","alias_value":"2412.06285v1","created_at":"2026-07-05T09:46:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.06285","created_at":"2026-07-05T09:46:18Z"},{"alias_kind":"pith_short_12","alias_value":"POGL2JWUZKIO","created_at":"2026-07-05T09:46:18Z"},{"alias_kind":"pith_short_16","alias_value":"POGL2JWUZKIOO3AI","created_at":"2026-07-05T09:46:18Z"},{"alias_kind":"pith_short_8","alias_value":"POGL2JWU","created_at":"2026-07-05T09:46:18Z"}],"graph_snapshots":[{"event_id":"sha256:fb5615af33d50b1eb082b203aa474fc816cb2002adf94e315cca560b539e5886","target":"graph","created_at":"2026-07-05T09:46:18Z","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/2412.06285/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Achieving efficient, high-fidelity, high-resolution garment simulation is challenging due to its computational demands. Conversely, low-resolution garment simulation is more accessible and ideal for low-budget devices like smartphones. In this paper, we introduce a lightweight, learning-based method for garment dynamic super-resolution, designed to efficiently enhance high-resolution, high-frequency details in low-resolution garment simulations. Starting with low-resolution garment simulation and underlying body motion, we utilize a mesh-graph-net to compute super-resolution features based on ","authors_text":"Jun Li, Meng Zhang","cross_cats":["cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T08:13:38Z","title":"Neural Garment Dynamic Super-Resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.06285","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":"sha256:2d31a1e48691edc80f6874096a56b241119ad060343ee81cfec960d4d12ea252","target":"record","created_at":"2026-07-05T09:46:18Z","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":"18814fa6bfa4801d72930f2c0ae1a7e66b67c4b111b1cecde44158eda51b4b6a","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T08:13:38Z","title_canon_sha256":"7fa6eb64c5ec6386439864b007b2d9c21e3c7aea24f3064e5fce9a560a251a8b"},"schema_version":"1.0","source":{"id":"2412.06285","kind":"arxiv","version":1}},"canonical_sha256":"7b8cbd26d4ca90e76c0867914d876914dea23bfc7050167450c6b1419ba6888d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b8cbd26d4ca90e76c0867914d876914dea23bfc7050167450c6b1419ba6888d","first_computed_at":"2026-07-05T09:46:18.522536Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:46:18.522536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5Ky50cyswKKU7oownu5NfJYkGbo5xlaeBP/9ykDA/UfHl1o1Mj1aQw6/714ugGUl1ihlHItEwWuY4/FEZvPCBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:46:18.523035Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.06285","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2d31a1e48691edc80f6874096a56b241119ad060343ee81cfec960d4d12ea252","sha256:fb5615af33d50b1eb082b203aa474fc816cb2002adf94e315cca560b539e5886"],"state_sha256":"a81c5f6d6df69688a3f3627862c5b597e1561f29b2400fb00d308f898a2644fd"}