{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:2MHU2BW2DRJQAW6HJRJSQRM6GK","short_pith_number":"pith:2MHU2BW2","schema_version":"1.0","canonical_sha256":"d30f4d06da1c53005bc74c5328459e32ad2058c3ccc96ba255674448c6c9b99d","source":{"kind":"arxiv","id":"2411.19525","version":2},"attestation_state":"computed","paper":{"title":"LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Bonan Li, Jingdong Chen, Meng Wang, Ming Yang, Ruobing Zheng, Tianqi Li, Zicheng Zhang","submitted_at":"2024-11-29T07:49:44Z","abstract_excerpt":"Despite significant progress in talking head synthesis since the introduction of Neural Radiance Fields (NeRF), visual artifacts and high training costs persist as major obstacles to large-scale commercial adoption. We propose that identifying and establishing fine-grained and generalizable correspondences between driving signals and generated results can simultaneously resolve both problems. Here we present LokiTalk, a novel framework designed to enhance NeRF-based talking heads with lifelike facial dynamics and improved training efficiency. To achieve fine-grained correspondences, we introdu"},"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":"2411.19525","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-29T07:49:44Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"14d23be80f11d5475d62b1aa3e68198fcf12dce2260d478364ddbc35d718189d","abstract_canon_sha256":"5c26433ba41f0b0129da37c877e44b666d1309c634558f55726e5da504101266"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:08.033412Z","signature_b64":"ho5X1YfLpTYzLS1cgdkA7oLF8uuYqdvqvQykK+0pll/XIpda96sJKI3mn+1iS2guAaShFpD2U4bA/9hGyv3GCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d30f4d06da1c53005bc74c5328459e32ad2058c3ccc96ba255674448c6c9b99d","last_reissued_at":"2026-07-05T09:53:08.032974Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:08.032974Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Bonan Li, Jingdong Chen, Meng Wang, Ming Yang, Ruobing Zheng, Tianqi Li, Zicheng Zhang","submitted_at":"2024-11-29T07:49:44Z","abstract_excerpt":"Despite significant progress in talking head synthesis since the introduction of Neural Radiance Fields (NeRF), visual artifacts and high training costs persist as major obstacles to large-scale commercial adoption. We propose that identifying and establishing fine-grained and generalizable correspondences between driving signals and generated results can simultaneously resolve both problems. Here we present LokiTalk, a novel framework designed to enhance NeRF-based talking heads with lifelike facial dynamics and improved training efficiency. To achieve fine-grained correspondences, we introdu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.19525","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/2411.19525/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":"2411.19525","created_at":"2026-07-05T09:53:08.033026+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.19525v2","created_at":"2026-07-05T09:53:08.033026+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.19525","created_at":"2026-07-05T09:53:08.033026+00:00"},{"alias_kind":"pith_short_12","alias_value":"2MHU2BW2DRJQ","created_at":"2026-07-05T09:53:08.033026+00:00"},{"alias_kind":"pith_short_16","alias_value":"2MHU2BW2DRJQAW6H","created_at":"2026-07-05T09:53:08.033026+00:00"},{"alias_kind":"pith_short_8","alias_value":"2MHU2BW2","created_at":"2026-07-05T09:53:08.033026+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK","json":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK.json","graph_json":"https://pith.science/api/pith-number/2MHU2BW2DRJQAW6HJRJSQRM6GK/graph.json","events_json":"https://pith.science/api/pith-number/2MHU2BW2DRJQAW6HJRJSQRM6GK/events.json","paper":"https://pith.science/paper/2MHU2BW2"},"agent_actions":{"view_html":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK","download_json":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK.json","view_paper":"https://pith.science/paper/2MHU2BW2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.19525&json=true","fetch_graph":"https://pith.science/api/pith-number/2MHU2BW2DRJQAW6HJRJSQRM6GK/graph.json","fetch_events":"https://pith.science/api/pith-number/2MHU2BW2DRJQAW6HJRJSQRM6GK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK/action/storage_attestation","attest_author":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK/action/author_attestation","sign_citation":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK/action/citation_signature","submit_replication":"https://pith.science/pith/2MHU2BW2DRJQAW6HJRJSQRM6GK/action/replication_record"}},"created_at":"2026-07-05T09:53:08.033026+00:00","updated_at":"2026-07-05T09:53:08.033026+00:00"}