{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2MNRTZFT5RXS2X32PRK5PHXC2G","short_pith_number":"pith:2MNRTZFT","canonical_record":{"source":{"id":"2312.16197","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-23T02:52:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"962a7088bd7a121a2d7f0f79d975f7066d04ab2daad1b962ca3d873968769c44","abstract_canon_sha256":"298ac758dc41152013a60cac3b2b145b2339a25eaf465f8c03c3c29b686b005c"},"schema_version":"1.0"},"canonical_sha256":"d31b19e4b3ec6f2d5f7a7c55d79ee2d18e851faeb356d912fe24c3d4a6e0b81a","source":{"kind":"arxiv","id":"2312.16197","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.16197","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.16197v1","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.16197","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_12","alias_value":"2MNRTZFT5RXS","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"2MNRTZFT5RXS2X32","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"2MNRTZFT","created_at":"2026-07-05T07:28:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2MNRTZFT5RXS2X32PRK5PHXC2G","target":"record","payload":{"canonical_record":{"source":{"id":"2312.16197","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-23T02:52:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"962a7088bd7a121a2d7f0f79d975f7066d04ab2daad1b962ca3d873968769c44","abstract_canon_sha256":"298ac758dc41152013a60cac3b2b145b2339a25eaf465f8c03c3c29b686b005c"},"schema_version":"1.0"},"canonical_sha256":"d31b19e4b3ec6f2d5f7a7c55d79ee2d18e851faeb356d912fe24c3d4a6e0b81a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:28:14.207554Z","signature_b64":"kRTC0NsVxP1+7+CjFHPl7dVTl6legJYyEJN+c0g/IPjDH/ZzMZf6J+HcsXCWFLgAxRbAJff5NVjkJcGp/V32Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d31b19e4b3ec6f2d5f7a7c55d79ee2d18e851faeb356d912fe24c3d4a6e0b81a","last_reissued_at":"2026-07-05T07:28:14.207093Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:28:14.207093Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.16197","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":"2026-07-05T07:28:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T5FprAcVjuycvPxz9DaqHRXmYGohaYSDBPDyx4AnZNi1BmMLCh1+Ntt3lpV5C8ySg/YhE+sCJbTnBHQpxAlkDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:20:18.881424Z"},"content_sha256":"d113ea182261afbd35697fcb2aed79ebd27a1855dfddec907995602394f803a7","schema_version":"1.0","event_id":"sha256:d113ea182261afbd35697fcb2aed79ebd27a1855dfddec907995602394f803a7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2MNRTZFT5RXS2X32PRK5PHXC2G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"INFAMOUS-NeRF: ImproviNg FAce MOdeling Using Semantically-Aligned Hypernetworks with Neural Radiance Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Andrew Hou, Feng Liu, Michel Sarkis, Ning Bi, Xiaoming Liu, Yiying Tong, Zhiyuan Ren","submitted_at":"2023-12-23T02:52:12Z","abstract_excerpt":"We propose INFAMOUS-NeRF, an implicit morphable face model that introduces hypernetworks to NeRF to improve the representation power in the presence of many training subjects. At the same time, INFAMOUS-NeRF resolves the classic hypernetwork tradeoff of representation power and editability by learning semantically-aligned latent spaces despite the subject-specific models, all without requiring a large pretrained model. INFAMOUS-NeRF further introduces a novel constraint to improve NeRF rendering along the face boundary. Our constraint can leverage photometric surface rendering and multi-view s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.16197","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/2312.16197/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":"2026-07-05T07:28:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Sdm3T/rUcY5z4Dl9zJblRGoTdWdHQFVPYLsDZuOEqdCI+UYJmrYbbMTsaDVwTu/27hb7S1J+LhXfXgNujU0fBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:20:18.881829Z"},"content_sha256":"1b267f8384ab424e78f46035086b385cf6c2d0b7e64081b9ccbf1354e3a68f27","schema_version":"1.0","event_id":"sha256:1b267f8384ab424e78f46035086b385cf6c2d0b7e64081b9ccbf1354e3a68f27"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/bundle.json","state_url":"https://pith.science/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/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":"2026-07-08T23:20:18Z","links":{"resolver":"https://pith.science/pith/2MNRTZFT5RXS2X32PRK5PHXC2G","bundle":"https://pith.science/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/bundle.json","state":"https://pith.science/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2MNRTZFT5RXS2X32PRK5PHXC2G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2MNRTZFT5RXS2X32PRK5PHXC2G","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":"298ac758dc41152013a60cac3b2b145b2339a25eaf465f8c03c3c29b686b005c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-23T02:52:12Z","title_canon_sha256":"962a7088bd7a121a2d7f0f79d975f7066d04ab2daad1b962ca3d873968769c44"},"schema_version":"1.0","source":{"id":"2312.16197","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.16197","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.16197v1","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.16197","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_12","alias_value":"2MNRTZFT5RXS","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"2MNRTZFT5RXS2X32","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"2MNRTZFT","created_at":"2026-07-05T07:28:14Z"}],"graph_snapshots":[{"event_id":"sha256:1b267f8384ab424e78f46035086b385cf6c2d0b7e64081b9ccbf1354e3a68f27","target":"graph","created_at":"2026-07-05T07:28:14Z","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/2312.16197/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose INFAMOUS-NeRF, an implicit morphable face model that introduces hypernetworks to NeRF to improve the representation power in the presence of many training subjects. At the same time, INFAMOUS-NeRF resolves the classic hypernetwork tradeoff of representation power and editability by learning semantically-aligned latent spaces despite the subject-specific models, all without requiring a large pretrained model. INFAMOUS-NeRF further introduces a novel constraint to improve NeRF rendering along the face boundary. Our constraint can leverage photometric surface rendering and multi-view s","authors_text":"Andrew Hou, Feng Liu, Michel Sarkis, Ning Bi, Xiaoming Liu, Yiying Tong, Zhiyuan Ren","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-23T02:52:12Z","title":"INFAMOUS-NeRF: ImproviNg FAce MOdeling Using Semantically-Aligned Hypernetworks with Neural Radiance Fields"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.16197","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:d113ea182261afbd35697fcb2aed79ebd27a1855dfddec907995602394f803a7","target":"record","created_at":"2026-07-05T07:28:14Z","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":"298ac758dc41152013a60cac3b2b145b2339a25eaf465f8c03c3c29b686b005c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-12-23T02:52:12Z","title_canon_sha256":"962a7088bd7a121a2d7f0f79d975f7066d04ab2daad1b962ca3d873968769c44"},"schema_version":"1.0","source":{"id":"2312.16197","kind":"arxiv","version":1}},"canonical_sha256":"d31b19e4b3ec6f2d5f7a7c55d79ee2d18e851faeb356d912fe24c3d4a6e0b81a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d31b19e4b3ec6f2d5f7a7c55d79ee2d18e851faeb356d912fe24c3d4a6e0b81a","first_computed_at":"2026-07-05T07:28:14.207093Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:28:14.207093Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kRTC0NsVxP1+7+CjFHPl7dVTl6legJYyEJN+c0g/IPjDH/ZzMZf6J+HcsXCWFLgAxRbAJff5NVjkJcGp/V32Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:28:14.207554Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.16197","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d113ea182261afbd35697fcb2aed79ebd27a1855dfddec907995602394f803a7","sha256:1b267f8384ab424e78f46035086b385cf6c2d0b7e64081b9ccbf1354e3a68f27"],"state_sha256":"8831d058399249f7a1397592c3f4a46cac0eb0dbf578dd1b1f1f471c4c30a3e9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2gqUTVhqcKAYDvy9Lhauu7/sAYUfsovC2Q9CeVFsqtDorOsZKDu0vtxRBxK7EIqIQgjRjVTqkB2rjh+59FxeCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T23:20:18.884196Z","bundle_sha256":"39dc72c5886d4c1181b5f7e29310b5d530640a9baf1c6413da02af3e07378513"}}