{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KFDSRCF6KXUA6ZZ3H24UY5YLEA","short_pith_number":"pith:KFDSRCF6","canonical_record":{"source":{"id":"2410.07971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-10T14:29:00Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"bb801020875384010d5ff12188a54db1155ed78bb696f96fc60cd3c353d274a0","abstract_canon_sha256":"fe8b66ce7dcaf575a7e5f120d5f8f9283510f900b07ab10fca27305628117197"},"schema_version":"1.0"},"canonical_sha256":"51472888be55e80f673b3eb94c770b202387f70bbf1985107901934eee78fdb0","source":{"kind":"arxiv","id":"2410.07971","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.07971","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"arxiv_version","alias_value":"2410.07971v1","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.07971","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_12","alias_value":"KFDSRCF6KXUA","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_16","alias_value":"KFDSRCF6KXUA6ZZ3","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_8","alias_value":"KFDSRCF6","created_at":"2026-07-05T09:18:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KFDSRCF6KXUA6ZZ3H24UY5YLEA","target":"record","payload":{"canonical_record":{"source":{"id":"2410.07971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-10T14:29:00Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"bb801020875384010d5ff12188a54db1155ed78bb696f96fc60cd3c353d274a0","abstract_canon_sha256":"fe8b66ce7dcaf575a7e5f120d5f8f9283510f900b07ab10fca27305628117197"},"schema_version":"1.0"},"canonical_sha256":"51472888be55e80f673b3eb94c770b202387f70bbf1985107901934eee78fdb0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:18:46.845968Z","signature_b64":"+WqwDOLXMxwW4sI/lEC5C5xSQv6PhIXJhHb04AgH/+zonNNv3tp3RKIosAO78OGE5i74UhkmV8/5md57y8rJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"51472888be55e80f673b3eb94c770b202387f70bbf1985107901934eee78fdb0","last_reissued_at":"2026-07-05T09:18:46.845543Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:18:46.845543Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.07971","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":"2026-07-05T09:18:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iaaOmtypLO3gGFG1oh4ojX4R4EoWbrsJx8x1lzQl+YZg/qqg6kbuSDq9ujaFRF1Rtjy5i2LrlGUE/8fy+F9UCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:56:01.147642Z"},"content_sha256":"6389ccf5b2391752dd7697931e5025164b09f8338f0110c1c3a8b22d6bb69c4f","schema_version":"1.0","event_id":"sha256:6389ccf5b2391752dd7697931e5025164b09f8338f0110c1c3a8b22d6bb69c4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KFDSRCF6KXUA6ZZ3H24UY5YLEA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalizable and Animatable Gaussian Head Avatar","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Tatsuya Harada, Xuangeng Chu","submitted_at":"2024-10-10T14:29:00Z","abstract_excerpt":"In this paper, we propose Generalizable and Animatable Gaussian head Avatar (GAGAvatar) for one-shot animatable head avatar reconstruction. Existing methods rely on neural radiance fields, leading to heavy rendering consumption and low reenactment speeds. To address these limitations, we generate the parameters of 3D Gaussians from a single image in a single forward pass. The key innovation of our work is the proposed dual-lifting method, which produces high-fidelity 3D Gaussians that capture identity and facial details. Additionally, we leverage global image features and the 3D morphable mode"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.07971","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/2410.07971/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":"2026-07-05T09:18:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NWS2f0AIS1Ujp8FFpegGYeOA7KzljRPHs3KylUvxesAYzJuOSSzW8W9DDGYm5uNbN7DLFsUVYEaT3uO0hV0eCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:56:01.148224Z"},"content_sha256":"9f3d460f01841ea6dc38c04db05cdbeebfb87c9b0b9e6c04d1372cd7737a44fa","schema_version":"1.0","event_id":"sha256:9f3d460f01841ea6dc38c04db05cdbeebfb87c9b0b9e6c04d1372cd7737a44fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/bundle.json","state_url":"https://pith.science/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/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":"2026-08-09T05:56:01Z","links":{"resolver":"https://pith.science/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA","bundle":"https://pith.science/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/bundle.json","state":"https://pith.science/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KFDSRCF6KXUA6ZZ3H24UY5YLEA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KFDSRCF6KXUA6ZZ3H24UY5YLEA","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":"fe8b66ce7dcaf575a7e5f120d5f8f9283510f900b07ab10fca27305628117197","cross_cats_sorted":["cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-10T14:29:00Z","title_canon_sha256":"bb801020875384010d5ff12188a54db1155ed78bb696f96fc60cd3c353d274a0"},"schema_version":"1.0","source":{"id":"2410.07971","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.07971","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"arxiv_version","alias_value":"2410.07971v1","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.07971","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_12","alias_value":"KFDSRCF6KXUA","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_16","alias_value":"KFDSRCF6KXUA6ZZ3","created_at":"2026-07-05T09:18:46Z"},{"alias_kind":"pith_short_8","alias_value":"KFDSRCF6","created_at":"2026-07-05T09:18:46Z"}],"graph_snapshots":[{"event_id":"sha256:9f3d460f01841ea6dc38c04db05cdbeebfb87c9b0b9e6c04d1372cd7737a44fa","target":"graph","created_at":"2026-07-05T09:18:46Z","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/2410.07971/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose Generalizable and Animatable Gaussian head Avatar (GAGAvatar) for one-shot animatable head avatar reconstruction. Existing methods rely on neural radiance fields, leading to heavy rendering consumption and low reenactment speeds. To address these limitations, we generate the parameters of 3D Gaussians from a single image in a single forward pass. The key innovation of our work is the proposed dual-lifting method, which produces high-fidelity 3D Gaussians that capture identity and facial details. Additionally, we leverage global image features and the 3D morphable mode","authors_text":"Tatsuya Harada, Xuangeng Chu","cross_cats":["cs.GR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-10T14:29:00Z","title":"Generalizable and Animatable Gaussian Head Avatar"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.07971","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":"sha256:6389ccf5b2391752dd7697931e5025164b09f8338f0110c1c3a8b22d6bb69c4f","target":"record","created_at":"2026-07-05T09:18:46Z","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":"fe8b66ce7dcaf575a7e5f120d5f8f9283510f900b07ab10fca27305628117197","cross_cats_sorted":["cs.GR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-10T14:29:00Z","title_canon_sha256":"bb801020875384010d5ff12188a54db1155ed78bb696f96fc60cd3c353d274a0"},"schema_version":"1.0","source":{"id":"2410.07971","kind":"arxiv","version":1}},"canonical_sha256":"51472888be55e80f673b3eb94c770b202387f70bbf1985107901934eee78fdb0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"51472888be55e80f673b3eb94c770b202387f70bbf1985107901934eee78fdb0","first_computed_at":"2026-07-05T09:18:46.845543Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:18:46.845543Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+WqwDOLXMxwW4sI/lEC5C5xSQv6PhIXJhHb04AgH/+zonNNv3tp3RKIosAO78OGE5i74UhkmV8/5md57y8rJBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:18:46.845968Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.07971","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6389ccf5b2391752dd7697931e5025164b09f8338f0110c1c3a8b22d6bb69c4f","sha256:9f3d460f01841ea6dc38c04db05cdbeebfb87c9b0b9e6c04d1372cd7737a44fa"],"state_sha256":"d6221776bf5a5cb83bf7d935d5b26f919e01852ed3a282f064abb8e764a601f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EQr/9v/TBYtadi+i2s1rZ7c93FMYcIrzb5M5fXg4kS/zrTau9c03Sb+e3ISBvA5Warmyx+tbILxI4EQLQ/MlAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:56:01.151506Z","bundle_sha256":"97680332c79f49092b0fab9f0b54fbd9deabaa748d3335d58191e028af279e74"}}