{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:E3YHB5KPM7RKLZQFGHUAFGR23G","short_pith_number":"pith:E3YHB5KP","canonical_record":{"source":{"id":"2304.03903","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T04:01:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"da2f8514277c8b3657f612ffbac51597c29fad1174019eed01fcaf5a6ff41823","abstract_canon_sha256":"9f50c632e737be087ff013ab76c469f75181fa063ce6d7d6f91c858e91971682"},"schema_version":"1.0"},"canonical_sha256":"26f070f54f67e2a5e60531e8029a3ad984a9b7a1664b36682c6575624a1a2813","source":{"kind":"arxiv","id":"2304.03903","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.03903","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"arxiv_version","alias_value":"2304.03903v1","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.03903","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_12","alias_value":"E3YHB5KPM7RK","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_16","alias_value":"E3YHB5KPM7RKLZQF","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_8","alias_value":"E3YHB5KP","created_at":"2026-07-05T05:59:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:E3YHB5KPM7RKLZQFGHUAFGR23G","target":"record","payload":{"canonical_record":{"source":{"id":"2304.03903","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T04:01:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"da2f8514277c8b3657f612ffbac51597c29fad1174019eed01fcaf5a6ff41823","abstract_canon_sha256":"9f50c632e737be087ff013ab76c469f75181fa063ce6d7d6f91c858e91971682"},"schema_version":"1.0"},"canonical_sha256":"26f070f54f67e2a5e60531e8029a3ad984a9b7a1664b36682c6575624a1a2813","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:08.907143Z","signature_b64":"V3lF1+5uhnlSdU0HGIUjttLz1uTGnVv5qoofFV1GrGvUI6hzGoDHAjwlosq4pSt0B2A73QkVscbPNgzzD/UxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"26f070f54f67e2a5e60531e8029a3ad984a9b7a1664b36682c6575624a1a2813","last_reissued_at":"2026-07-05T05:59:08.906792Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:08.906792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.03903","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":"2026-07-05T05:59:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eg9nyLES191SS14IacT8GjHMEXW7DtCLweUfF65CirX6bafQn8c2fad/9Y9UMXZuCWgJWeXM+Bm2tghoAEMdAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T12:43:47.256247Z"},"content_sha256":"283d09d853b7653cb5d04d81e3965d718d0b64f8a8683ea0e993b5e97135fe16","schema_version":"1.0","event_id":"sha256:283d09d853b7653cb5d04d81e3965d718d0b64f8a8683ea0e993b5e97135fe16"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:E3YHB5KPM7RKLZQFGHUAFGR23G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"High-Fidelity Clothed Avatar Reconstruction from a Single Image","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Guo-jun Qi, Hongwei Yi, Tingting Liao, Xiangyu Zhu, Xiaomei Zhang, Xuan Wang, Xudong Liu, Yong Zhang, Yuliang Xiu, Zhen Lei","submitted_at":"2023-04-08T04:01:04Z","abstract_excerpt":"This paper presents a framework for efficient 3D clothed avatar reconstruction. By combining the advantages of the high accuracy of optimization-based methods and the efficiency of learning-based methods, we propose a coarse-to-fine way to realize a high-fidelity clothed avatar reconstruction (CAR) from a single image. At the first stage, we use an implicit model to learn the general shape in the canonical space of a person in a learning-based way, and at the second stage, we refine the surface detail by estimating the non-rigid deformation in the posed space in an optimization way. A hyper-ne"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.03903","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/2304.03903/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":"2026-07-05T05:59:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Vt4v2YKcd9UEBplW4KQFJW6yYwund+gOQI3hZhRB9rIvI8IhTX6PZoTCVdlPorQyN01yPCXiHb6cRZdXlFVAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T12:43:47.256819Z"},"content_sha256":"6cfa782df586021fd75d9ea9c85427f330d2ae1f5c85d07ed5175cc03e5d6b75","schema_version":"1.0","event_id":"sha256:6cfa782df586021fd75d9ea9c85427f330d2ae1f5c85d07ed5175cc03e5d6b75"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/bundle.json","state_url":"https://pith.science/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/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":"2026-08-19T12:43:47Z","links":{"resolver":"https://pith.science/pith/E3YHB5KPM7RKLZQFGHUAFGR23G","bundle":"https://pith.science/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/bundle.json","state":"https://pith.science/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E3YHB5KPM7RKLZQFGHUAFGR23G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:E3YHB5KPM7RKLZQFGHUAFGR23G","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":"9f50c632e737be087ff013ab76c469f75181fa063ce6d7d6f91c858e91971682","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T04:01:04Z","title_canon_sha256":"da2f8514277c8b3657f612ffbac51597c29fad1174019eed01fcaf5a6ff41823"},"schema_version":"1.0","source":{"id":"2304.03903","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.03903","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"arxiv_version","alias_value":"2304.03903v1","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.03903","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_12","alias_value":"E3YHB5KPM7RK","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_16","alias_value":"E3YHB5KPM7RKLZQF","created_at":"2026-07-05T05:59:08Z"},{"alias_kind":"pith_short_8","alias_value":"E3YHB5KP","created_at":"2026-07-05T05:59:08Z"}],"graph_snapshots":[{"event_id":"sha256:6cfa782df586021fd75d9ea9c85427f330d2ae1f5c85d07ed5175cc03e5d6b75","target":"graph","created_at":"2026-07-05T05:59:08Z","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/2304.03903/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a framework for efficient 3D clothed avatar reconstruction. By combining the advantages of the high accuracy of optimization-based methods and the efficiency of learning-based methods, we propose a coarse-to-fine way to realize a high-fidelity clothed avatar reconstruction (CAR) from a single image. At the first stage, we use an implicit model to learn the general shape in the canonical space of a person in a learning-based way, and at the second stage, we refine the surface detail by estimating the non-rigid deformation in the posed space in an optimization way. A hyper-ne","authors_text":"Guo-jun Qi, Hongwei Yi, Tingting Liao, Xiangyu Zhu, Xiaomei Zhang, Xuan Wang, Xudong Liu, Yong Zhang, Yuliang Xiu, Zhen Lei","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T04:01:04Z","title":"High-Fidelity Clothed Avatar Reconstruction from a Single Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.03903","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":"sha256:283d09d853b7653cb5d04d81e3965d718d0b64f8a8683ea0e993b5e97135fe16","target":"record","created_at":"2026-07-05T05:59:08Z","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":"9f50c632e737be087ff013ab76c469f75181fa063ce6d7d6f91c858e91971682","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T04:01:04Z","title_canon_sha256":"da2f8514277c8b3657f612ffbac51597c29fad1174019eed01fcaf5a6ff41823"},"schema_version":"1.0","source":{"id":"2304.03903","kind":"arxiv","version":1}},"canonical_sha256":"26f070f54f67e2a5e60531e8029a3ad984a9b7a1664b36682c6575624a1a2813","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26f070f54f67e2a5e60531e8029a3ad984a9b7a1664b36682c6575624a1a2813","first_computed_at":"2026-07-05T05:59:08.906792Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:08.906792Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V3lF1+5uhnlSdU0HGIUjttLz1uTGnVv5qoofFV1GrGvUI6hzGoDHAjwlosq4pSt0B2A73QkVscbPNgzzD/UxDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:08.907143Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.03903","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:283d09d853b7653cb5d04d81e3965d718d0b64f8a8683ea0e993b5e97135fe16","sha256:6cfa782df586021fd75d9ea9c85427f330d2ae1f5c85d07ed5175cc03e5d6b75"],"state_sha256":"2bd2c78921b6b50456bc21cfcb67ceb642239ad72e3b97298fd4a6072a422e63"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3DeYl61b8SqvosuYLojlL+x+FNA0HNA3Al+hVN7hNd5uDxQNVn+MAlwP0C03TYCov78tpps0OBSF3wvyD/rtCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T12:43:47.261778Z","bundle_sha256":"c92e9ab2a6df602a5c14c25a791373881172c409872599aeb76285b6a5eb2dca"}}