{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:A2IB5BMMH4YUHVGRBCNWXU7URR","short_pith_number":"pith:A2IB5BMM","schema_version":"1.0","canonical_sha256":"06901e858c3f3143d4d1089b6bd3f48c5363b6131e9bbfc051ba5351fed362bb","source":{"kind":"arxiv","id":"2501.05379","version":2},"attestation_state":"computed","paper":{"title":"Arc2Avatar: Generating Expressive 3D Avatars from a Single Image via ID Guidance","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexandros Lattas, Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias, Stefanos Zafeiriou","submitted_at":"2025-01-09T17:04:33Z","abstract_excerpt":"Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, we introduce Arc2Avatar, the first SDS-based method utilizing a human face foundation model as guidance with just a single image as input. To achieve that, we extend such a model for diverse-view human head generation by fine-tuning on synthetic data and modifying its conditioning. Our avatars maintain a dense correspondence with a human face mesh template, allowing blendshape-based expression generation. This is achi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2501.05379","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-09T17:04:33Z","cross_cats_sorted":[],"title_canon_sha256":"1026abef2da14b1ff9f33c65278d37808c8dfb7a04353f0f64dcd919648f8f3d","abstract_canon_sha256":"caaf196abf0854630534eebff3b89b8ccce8623e28db4e45f48b7229287021c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:27.210637Z","signature_b64":"OMmkToHR0NwaEnRLkleDGNAasDnDpeJA35uSLTrdBTGzerQ4ivGBNPAZR+v4GvDITPURqdnlJg605yQNXIHtBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"06901e858c3f3143d4d1089b6bd3f48c5363b6131e9bbfc051ba5351fed362bb","last_reissued_at":"2026-07-05T10:00:27.210156Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:27.210156Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Arc2Avatar: Generating Expressive 3D Avatars from a Single Image via ID Guidance","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexandros Lattas, Dimitrios Gerogiannis, Foivos Paraperas Papantoniou, Rolandos Alexandros Potamias, Stefanos Zafeiriou","submitted_at":"2025-01-09T17:04:33Z","abstract_excerpt":"Inspired by the effectiveness of 3D Gaussian Splatting (3DGS) in reconstructing detailed 3D scenes within multi-view setups and the emergence of large 2D human foundation models, we introduce Arc2Avatar, the first SDS-based method utilizing a human face foundation model as guidance with just a single image as input. To achieve that, we extend such a model for diverse-view human head generation by fine-tuning on synthetic data and modifying its conditioning. Our avatars maintain a dense correspondence with a human face mesh template, allowing blendshape-based expression generation. This is achi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.05379","kind":"arxiv","version":2},"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/2501.05379/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2501.05379","created_at":"2026-07-05T10:00:27.210216+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.05379v2","created_at":"2026-07-05T10:00:27.210216+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.05379","created_at":"2026-07-05T10:00:27.210216+00:00"},{"alias_kind":"pith_short_12","alias_value":"A2IB5BMMH4YU","created_at":"2026-07-05T10:00:27.210216+00:00"},{"alias_kind":"pith_short_16","alias_value":"A2IB5BMMH4YUHVGR","created_at":"2026-07-05T10:00:27.210216+00:00"},{"alias_kind":"pith_short_8","alias_value":"A2IB5BMM","created_at":"2026-07-05T10:00:27.210216+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2511.02777","citing_title":"PercHead: Perceptual Head Model for Single-Image 3D Head Reconstruction & Editing","ref_index":17,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR","json":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR.json","graph_json":"https://pith.science/api/pith-number/A2IB5BMMH4YUHVGRBCNWXU7URR/graph.json","events_json":"https://pith.science/api/pith-number/A2IB5BMMH4YUHVGRBCNWXU7URR/events.json","paper":"https://pith.science/paper/A2IB5BMM"},"agent_actions":{"view_html":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR","download_json":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR.json","view_paper":"https://pith.science/paper/A2IB5BMM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.05379&json=true","fetch_graph":"https://pith.science/api/pith-number/A2IB5BMMH4YUHVGRBCNWXU7URR/graph.json","fetch_events":"https://pith.science/api/pith-number/A2IB5BMMH4YUHVGRBCNWXU7URR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR/action/storage_attestation","attest_author":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR/action/author_attestation","sign_citation":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR/action/citation_signature","submit_replication":"https://pith.science/pith/A2IB5BMMH4YUHVGRBCNWXU7URR/action/replication_record"}},"created_at":"2026-07-05T10:00:27.210216+00:00","updated_at":"2026-07-05T10:00:27.210216+00:00"}