{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7BUPL6IBIYYQ7MIQMWYKE5PXS6","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":"526ca11fd251eb25def5f29351fcff8628405af7ab75ffeca01917b37ef75fb8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T05:10:59Z","title_canon_sha256":"47fad89fc04d5026beeee315c02174af1a87ada4d80ce4aa77a930eff5735892"},"schema_version":"1.0","source":{"id":"2402.17214","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.17214","created_at":"2026-07-05T08:42:22Z"},{"alias_kind":"arxiv_version","alias_value":"2402.17214v3","created_at":"2026-07-05T08:42:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.17214","created_at":"2026-07-05T08:42:22Z"},{"alias_kind":"pith_short_12","alias_value":"7BUPL6IBIYYQ","created_at":"2026-07-05T08:42:22Z"},{"alias_kind":"pith_short_16","alias_value":"7BUPL6IBIYYQ7MIQ","created_at":"2026-07-05T08:42:22Z"},{"alias_kind":"pith_short_8","alias_value":"7BUPL6IB","created_at":"2026-07-05T08:42:22Z"}],"graph_snapshots":[{"event_id":"sha256:0423f711d0c1049841bceefdc4ec9512cbc0e21bb9b73b64b9a366aeebb385bf","target":"graph","created_at":"2026-07-05T08:42:22Z","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/2402.17214/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the field of digital content creation, generating high-quality 3D characters from single images is challenging, especially given the complexities of various body poses and the issues of self-occlusion and pose ambiguity. In this paper, we present CharacterGen, a framework developed to efficiently generate 3D characters. CharacterGen introduces a streamlined generation pipeline along with an image-conditioned multi-view diffusion model. This model effectively calibrates input poses to a canonical form while retaining key attributes of the input image, thereby addressing the challenges posed ","authors_text":"Hao-Yang Peng, Jia-Peng Zhang, Meng-Hao Guo, Shi-Min Hu, Yan-Pei Cao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T05:10:59Z","title":"CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.17214","kind":"arxiv","version":3},"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:d5dcba5b7c184e3a518f00f619b9fc8310f70ff9eea19cbc9fc0f8250c121f65","target":"record","created_at":"2026-07-05T08:42:22Z","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":"526ca11fd251eb25def5f29351fcff8628405af7ab75ffeca01917b37ef75fb8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-02-27T05:10:59Z","title_canon_sha256":"47fad89fc04d5026beeee315c02174af1a87ada4d80ce4aa77a930eff5735892"},"schema_version":"1.0","source":{"id":"2402.17214","kind":"arxiv","version":3}},"canonical_sha256":"f868f5f90146310fb11065b0a275f79793d92d3a744b7f75f0140eea3d0c6d1a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f868f5f90146310fb11065b0a275f79793d92d3a744b7f75f0140eea3d0c6d1a","first_computed_at":"2026-07-05T08:42:22.052183Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:42:22.052183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fKD/xcX8uZB9KLlhV2fPL5Fq3ilez0515A85pn6LYOmm/fvderaWY5/71xAjPdjO4+qBkUEeE0JNpdkOKZnNCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:42:22.052647Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.17214","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5dcba5b7c184e3a518f00f619b9fc8310f70ff9eea19cbc9fc0f8250c121f65","sha256:0423f711d0c1049841bceefdc4ec9512cbc0e21bb9b73b64b9a366aeebb385bf"],"state_sha256":"9b498dd2027d797a863ae7d916135e37c832264bcc9df468b765acc932cde515"}