{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:OGIX7OX6LDCTZVLVNMAJHJY6NP","short_pith_number":"pith:OGIX7OX6","canonical_record":{"source":{"id":"2303.09375","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T15:04:10Z","cross_cats_sorted":[],"title_canon_sha256":"a88800d1731ca1bc4edb15969d92ad80c5fcd92bdbede9aa34a506c83e77ce81","abstract_canon_sha256":"662240a6406c3fa1f7282e8b66b06a616d5a947b677b8d7b2ad1f8dad2fb4fd3"},"schema_version":"1.0"},"canonical_sha256":"71917fbafe58c53cd5756b0093a71e6bd543c88314de8e2deb61a391f818b04f","source":{"kind":"arxiv","id":"2303.09375","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09375","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09375v4","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09375","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_12","alias_value":"OGIX7OX6LDCT","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_16","alias_value":"OGIX7OX6LDCTZVLV","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_8","alias_value":"OGIX7OX6","created_at":"2026-07-05T07:22:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:OGIX7OX6LDCTZVLVNMAJHJY6NP","target":"record","payload":{"canonical_record":{"source":{"id":"2303.09375","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T15:04:10Z","cross_cats_sorted":[],"title_canon_sha256":"a88800d1731ca1bc4edb15969d92ad80c5fcd92bdbede9aa34a506c83e77ce81","abstract_canon_sha256":"662240a6406c3fa1f7282e8b66b06a616d5a947b677b8d7b2ad1f8dad2fb4fd3"},"schema_version":"1.0"},"canonical_sha256":"71917fbafe58c53cd5756b0093a71e6bd543c88314de8e2deb61a391f818b04f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:22:16.207610Z","signature_b64":"2wK19svPwUENr5Hmy0oJQ1JMWxjC0g5l1iX+4sFyQDd95+zDA5u19kXtptl2rdHNwgatKy6CC2qb4Y0LE3aRCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71917fbafe58c53cd5756b0093a71e6bd543c88314de8e2deb61a391f818b04f","last_reissued_at":"2026-07-05T07:22:16.207110Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:22:16.207110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.09375","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:22:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FKA7vm8ETl9vdWMa+8WsFPaRqrt6JCkrvkuLQOacS+OBQCkVt5H8KpSpB1l+Frmjhi957std1ySqxY6W1iheBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:26:03.478822Z"},"content_sha256":"5b798333cd80f7c7188bb305e04fa581d652d5ea2bf43ad9f19fe64fe8c1b6cd","schema_version":"1.0","event_id":"sha256:5b798333cd80f7c7188bb305e04fa581d652d5ea2bf43ad9f19fe64fe8c1b6cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:OGIX7OX6LDCTZVLVNMAJHJY6NP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DINAR: Diffusion Inpainting of Neural Textures for One-Shot Human Avatars","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"David Svitov, Dmitrii Gudkov, Renat Bashirov, Victor Lempitsky","submitted_at":"2023-03-16T15:04:10Z","abstract_excerpt":"We present DINAR, an approach for creating realistic rigged fullbody avatars from single RGB images. Similarly to previous works, our method uses neural textures combined with the SMPL-X body model to achieve photo-realistic quality of avatars while keeping them easy to animate and fast to infer. To restore the texture, we use a latent diffusion model and show how such model can be trained in the neural texture space. The use of the diffusion model allows us to realistically reconstruct large unseen regions such as the back of a person given the frontal view. The models in our pipeline are tra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09375","kind":"arxiv","version":4},"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/2303.09375/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":"2026-07-05T07:22:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RHIQILYWyNGZSIsPgfKQT8KQ2gK1dWVEiwdYgLxL1ZitqrVqW6qRcex1f6uBHg0T32XRhdRUzKJJXXSqzz99Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:26:03.479225Z"},"content_sha256":"26c8e8a04f4b83c5ee4e41454d8abfc509d214488d8d3ad048bac8d45e658cd1","schema_version":"1.0","event_id":"sha256:26c8e8a04f4b83c5ee4e41454d8abfc509d214488d8d3ad048bac8d45e658cd1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/bundle.json","state_url":"https://pith.science/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/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":"2026-07-06T23:26:03Z","links":{"resolver":"https://pith.science/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP","bundle":"https://pith.science/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/bundle.json","state":"https://pith.science/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OGIX7OX6LDCTZVLVNMAJHJY6NP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:OGIX7OX6LDCTZVLVNMAJHJY6NP","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":"662240a6406c3fa1f7282e8b66b06a616d5a947b677b8d7b2ad1f8dad2fb4fd3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T15:04:10Z","title_canon_sha256":"a88800d1731ca1bc4edb15969d92ad80c5fcd92bdbede9aa34a506c83e77ce81"},"schema_version":"1.0","source":{"id":"2303.09375","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09375","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09375v4","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09375","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_12","alias_value":"OGIX7OX6LDCT","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_16","alias_value":"OGIX7OX6LDCTZVLV","created_at":"2026-07-05T07:22:16Z"},{"alias_kind":"pith_short_8","alias_value":"OGIX7OX6","created_at":"2026-07-05T07:22:16Z"}],"graph_snapshots":[{"event_id":"sha256:26c8e8a04f4b83c5ee4e41454d8abfc509d214488d8d3ad048bac8d45e658cd1","target":"graph","created_at":"2026-07-05T07:22:16Z","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/2303.09375/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present DINAR, an approach for creating realistic rigged fullbody avatars from single RGB images. Similarly to previous works, our method uses neural textures combined with the SMPL-X body model to achieve photo-realistic quality of avatars while keeping them easy to animate and fast to infer. To restore the texture, we use a latent diffusion model and show how such model can be trained in the neural texture space. The use of the diffusion model allows us to realistically reconstruct large unseen regions such as the back of a person given the frontal view. The models in our pipeline are tra","authors_text":"David Svitov, Dmitrii Gudkov, Renat Bashirov, Victor Lempitsky","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T15:04:10Z","title":"DINAR: Diffusion Inpainting of Neural Textures for One-Shot Human Avatars"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09375","kind":"arxiv","version":4},"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":"sha256:5b798333cd80f7c7188bb305e04fa581d652d5ea2bf43ad9f19fe64fe8c1b6cd","target":"record","created_at":"2026-07-05T07:22:16Z","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":"662240a6406c3fa1f7282e8b66b06a616d5a947b677b8d7b2ad1f8dad2fb4fd3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T15:04:10Z","title_canon_sha256":"a88800d1731ca1bc4edb15969d92ad80c5fcd92bdbede9aa34a506c83e77ce81"},"schema_version":"1.0","source":{"id":"2303.09375","kind":"arxiv","version":4}},"canonical_sha256":"71917fbafe58c53cd5756b0093a71e6bd543c88314de8e2deb61a391f818b04f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"71917fbafe58c53cd5756b0093a71e6bd543c88314de8e2deb61a391f818b04f","first_computed_at":"2026-07-05T07:22:16.207110Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:22:16.207110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2wK19svPwUENr5Hmy0oJQ1JMWxjC0g5l1iX+4sFyQDd95+zDA5u19kXtptl2rdHNwgatKy6CC2qb4Y0LE3aRCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:22:16.207610Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.09375","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b798333cd80f7c7188bb305e04fa581d652d5ea2bf43ad9f19fe64fe8c1b6cd","sha256:26c8e8a04f4b83c5ee4e41454d8abfc509d214488d8d3ad048bac8d45e658cd1"],"state_sha256":"6d467aee22f5b3d3f9c3cae64321e06c517b4a2e558705fbb5bc27fc5f3e92a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eq+708LPo1mh9T8FOE39KIXaSuqfh1EO/Yd0iABxJI+dv9II+wVvrM88rbRgov2lE9aPPN2trbqCvyLjksQfAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T23:26:03.481132Z","bundle_sha256":"2c975104d07741c573df2a43575a662073115d2db86a58d188bacb53acf662cd"}}