{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YDI4PM4BAQ3QYYCLRLAYTP3ZKY","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":"610836180c2b203503f56e2f734605f34ff19408f24538fe69733d225ab0473e","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GR","submitted_at":"2025-01-14T18:40:33Z","title_canon_sha256":"9320464730b6aac17ce78a386e9dab612cbc25408a57f2bed4519076dd5baa42"},"schema_version":"1.0","source":{"id":"2501.08370","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.08370","created_at":"2026-07-05T10:01:01Z"},{"alias_kind":"arxiv_version","alias_value":"2501.08370v1","created_at":"2026-07-05T10:01:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.08370","created_at":"2026-07-05T10:01:01Z"},{"alias_kind":"pith_short_12","alias_value":"YDI4PM4BAQ3Q","created_at":"2026-07-05T10:01:01Z"},{"alias_kind":"pith_short_16","alias_value":"YDI4PM4BAQ3QYYCL","created_at":"2026-07-05T10:01:01Z"},{"alias_kind":"pith_short_8","alias_value":"YDI4PM4B","created_at":"2026-07-05T10:01:01Z"}],"graph_snapshots":[{"event_id":"sha256:1b079d9ea2ac783fcdb9bdc8ddb3ce4352920a78dc67b819cf2f59195ad63ffa","target":"graph","created_at":"2026-07-05T10:01:01Z","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/2501.08370/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Differentiable 3D Gaussian splatting has emerged as an efficient and flexible rendering technique for representing complex scenes from a collection of 2D views and enabling high-quality real-time novel-view synthesis. However, its reliance on photometric losses can lead to imprecisely reconstructed geometry and extracted meshes, especially in regions with high curvature or fine detail. We propose a novel regularization method using the gradients of a signed distance function estimated from the Gaussians, to improve the quality of rendering while also extracting a surface mesh. The regularizing","authors_text":"Liam Fowl, Meenakshi Krishnan, Ramani Duraiswami","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GR","submitted_at":"2025-01-14T18:40:33Z","title":"3D Gaussian Splatting with Normal Information for Mesh Extraction and Improved Rendering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.08370","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:e105ce02cf308ca3c42183de4d90c272ff300fa9b15985b03f66d1502ba13516","target":"record","created_at":"2026-07-05T10:01:01Z","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":"610836180c2b203503f56e2f734605f34ff19408f24538fe69733d225ab0473e","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GR","submitted_at":"2025-01-14T18:40:33Z","title_canon_sha256":"9320464730b6aac17ce78a386e9dab612cbc25408a57f2bed4519076dd5baa42"},"schema_version":"1.0","source":{"id":"2501.08370","kind":"arxiv","version":1}},"canonical_sha256":"c0d1c7b38104370c604b8ac189bf79560ed171bc4266b474cca36f0143ae9601","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0d1c7b38104370c604b8ac189bf79560ed171bc4266b474cca36f0143ae9601","first_computed_at":"2026-07-05T10:01:01.749037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:01:01.749037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w9rSzLqSDUWKkQKZsaQaNrrY5R+Q61+nKtitn6r3Atr1nV3gQzKwgkTKhJhWplUZElnPOoptD7wWzc/p3GtUBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:01:01.749414Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.08370","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e105ce02cf308ca3c42183de4d90c272ff300fa9b15985b03f66d1502ba13516","sha256:1b079d9ea2ac783fcdb9bdc8ddb3ce4352920a78dc67b819cf2f59195ad63ffa"],"state_sha256":"c269d4bd05e9ba18c661baa0142ca7b8405408c28e9393050a0cf6808b3a7450"}