{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:G3C2GW35UHQYZY26T6IFKAXMVY","short_pith_number":"pith:G3C2GW35","canonical_record":{"source":{"id":"2209.08468","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2022-09-18T03:58:00Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"8dd4662f516526ddb5c61de19ceaf554d89b9a7cd4da2735f7aa7a0e776b63a0","abstract_canon_sha256":"007468d9fcceb5984c3f8bb51835834cbb3ee4f443e172ffcac8e38b11d2e0f6"},"schema_version":"1.0"},"canonical_sha256":"36c5a35b7da1e18ce35e9f905502ecae3f29065b0854d389c9e8b35cc01c67e4","source":{"kind":"arxiv","id":"2209.08468","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.08468","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"arxiv_version","alias_value":"2209.08468v1","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.08468","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_12","alias_value":"G3C2GW35UHQY","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_16","alias_value":"G3C2GW35UHQYZY26","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_8","alias_value":"G3C2GW35","created_at":"2026-07-05T04:58:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:G3C2GW35UHQYZY26T6IFKAXMVY","target":"record","payload":{"canonical_record":{"source":{"id":"2209.08468","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2022-09-18T03:58:00Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"8dd4662f516526ddb5c61de19ceaf554d89b9a7cd4da2735f7aa7a0e776b63a0","abstract_canon_sha256":"007468d9fcceb5984c3f8bb51835834cbb3ee4f443e172ffcac8e38b11d2e0f6"},"schema_version":"1.0"},"canonical_sha256":"36c5a35b7da1e18ce35e9f905502ecae3f29065b0854d389c9e8b35cc01c67e4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:58:41.818255Z","signature_b64":"kd/CXMsFGZq9oV9y+qOtm6S04X2F+9/UJ+P13HNknK3n6K3MPcnE0AMfXkKhwPuKJTCurB8N3UH1Yk8/MdvVBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36c5a35b7da1e18ce35e9f905502ecae3f29065b0854d389c9e8b35cc01c67e4","last_reissued_at":"2026-07-05T04:58:41.817812Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:58:41.817812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.08468","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:58:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f18QYenmDgTmO4xpUQh43on5aIxrLjt4io3uEfQ96jIe+qmYBZXwDvwKd1469+p9D3Ip7ozZF3cRsvzbIU5iAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T09:27:14.334516Z"},"content_sha256":"c9eec69ff5109efc24768472197ef9a7f27acca1a813d6e0719ea0a9d28893c0","schema_version":"1.0","event_id":"sha256:c9eec69ff5109efc24768472197ef9a7f27acca1a813d6e0719ea0a9d28893c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:G3C2GW35UHQYZY26T6IFKAXMVY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Human Performance Modeling and Rendering via Neural Animated Mesh","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.GR","authors_text":"Fuqiang Zhao, Haizhao Dai, Jiakai Zhang, Jingyi Yu, Kaixin Yao, Lan Xu, Liao Wang, Minye Wu, Yingliang Zhang, Yuheng Jiang, Yuhui Zhong","submitted_at":"2022-09-18T03:58:00Z","abstract_excerpt":"We have recently seen tremendous progress in the neural advances for photo-real human modeling and rendering. However, it's still challenging to integrate them into an existing mesh-based pipeline for downstream applications. In this paper, we present a comprehensive neural approach for high-quality reconstruction, compression, and rendering of human performances from dense multi-view videos. Our core intuition is to bridge the traditional animated mesh workflow with a new class of highly efficient neural techniques. We first introduce a neural surface reconstructor for high-quality surface ge"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.08468","kind":"arxiv","version":1},"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/2209.08468/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":"2026-07-05T04:58:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6c23n0OfyspDqCWURXbgM+KN8LN+GtRveMCsggpuJRiKgoJhlXtxw6/bE0hxR+sDNo0AUi27uwiMMUOiRxfzDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T09:27:14.334885Z"},"content_sha256":"ac5578f9a8a8cbe38f9dcf647c423ee77ad27a94d5392977b24fadac42530a1a","schema_version":"1.0","event_id":"sha256:ac5578f9a8a8cbe38f9dcf647c423ee77ad27a94d5392977b24fadac42530a1a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G3C2GW35UHQYZY26T6IFKAXMVY/bundle.json","state_url":"https://pith.science/pith/G3C2GW35UHQYZY26T6IFKAXMVY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G3C2GW35UHQYZY26T6IFKAXMVY/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":"2026-07-05T09:27:14Z","links":{"resolver":"https://pith.science/pith/G3C2GW35UHQYZY26T6IFKAXMVY","bundle":"https://pith.science/pith/G3C2GW35UHQYZY26T6IFKAXMVY/bundle.json","state":"https://pith.science/pith/G3C2GW35UHQYZY26T6IFKAXMVY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G3C2GW35UHQYZY26T6IFKAXMVY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:G3C2GW35UHQYZY26T6IFKAXMVY","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":"007468d9fcceb5984c3f8bb51835834cbb3ee4f443e172ffcac8e38b11d2e0f6","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2022-09-18T03:58:00Z","title_canon_sha256":"8dd4662f516526ddb5c61de19ceaf554d89b9a7cd4da2735f7aa7a0e776b63a0"},"schema_version":"1.0","source":{"id":"2209.08468","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.08468","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"arxiv_version","alias_value":"2209.08468v1","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.08468","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_12","alias_value":"G3C2GW35UHQY","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_16","alias_value":"G3C2GW35UHQYZY26","created_at":"2026-07-05T04:58:41Z"},{"alias_kind":"pith_short_8","alias_value":"G3C2GW35","created_at":"2026-07-05T04:58:41Z"}],"graph_snapshots":[{"event_id":"sha256:ac5578f9a8a8cbe38f9dcf647c423ee77ad27a94d5392977b24fadac42530a1a","target":"graph","created_at":"2026-07-05T04:58:41Z","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/2209.08468/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We have recently seen tremendous progress in the neural advances for photo-real human modeling and rendering. However, it's still challenging to integrate them into an existing mesh-based pipeline for downstream applications. In this paper, we present a comprehensive neural approach for high-quality reconstruction, compression, and rendering of human performances from dense multi-view videos. Our core intuition is to bridge the traditional animated mesh workflow with a new class of highly efficient neural techniques. We first introduce a neural surface reconstructor for high-quality surface ge","authors_text":"Fuqiang Zhao, Haizhao Dai, Jiakai Zhang, Jingyi Yu, Kaixin Yao, Lan Xu, Liao Wang, Minye Wu, Yingliang Zhang, Yuheng Jiang, Yuhui Zhong","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2022-09-18T03:58:00Z","title":"Human Performance Modeling and Rendering via Neural Animated Mesh"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.08468","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:c9eec69ff5109efc24768472197ef9a7f27acca1a813d6e0719ea0a9d28893c0","target":"record","created_at":"2026-07-05T04:58:41Z","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":"007468d9fcceb5984c3f8bb51835834cbb3ee4f443e172ffcac8e38b11d2e0f6","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2022-09-18T03:58:00Z","title_canon_sha256":"8dd4662f516526ddb5c61de19ceaf554d89b9a7cd4da2735f7aa7a0e776b63a0"},"schema_version":"1.0","source":{"id":"2209.08468","kind":"arxiv","version":1}},"canonical_sha256":"36c5a35b7da1e18ce35e9f905502ecae3f29065b0854d389c9e8b35cc01c67e4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36c5a35b7da1e18ce35e9f905502ecae3f29065b0854d389c9e8b35cc01c67e4","first_computed_at":"2026-07-05T04:58:41.817812Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:58:41.817812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kd/CXMsFGZq9oV9y+qOtm6S04X2F+9/UJ+P13HNknK3n6K3MPcnE0AMfXkKhwPuKJTCurB8N3UH1Yk8/MdvVBg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:58:41.818255Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.08468","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c9eec69ff5109efc24768472197ef9a7f27acca1a813d6e0719ea0a9d28893c0","sha256:ac5578f9a8a8cbe38f9dcf647c423ee77ad27a94d5392977b24fadac42530a1a"],"state_sha256":"95662d7faf6dcf00ef3c2b32f6d624bbc0f79cbf37d4d61a138f5da47c8a3dbd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wNcQBLjJGtyW1vVfgvLeWwtfhZ0P5Z+bvA6siHzS6sXO7FltR0pX5iaYXeMY3XM692ooPCSbpempgd3GUjOLAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T09:27:14.336910Z","bundle_sha256":"e096e9a46f51ee90c5d008328d051a2c42e503851a538f6c534e3a1067f1de37"}}