{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3VQ4ANCXC2O7VPBPJ4OOFCPL6S","short_pith_number":"pith:3VQ4ANCX","canonical_record":{"source":{"id":"1904.07528","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T08:15:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"968be4acd7c4762ffeb7b525fcc0906c55436769196aec10a2244ccbfdc2e9c7","abstract_canon_sha256":"649063c48b73b60a93e95cc3a0c6b37031b0667839bb7729f95356a6e6f8831f"},"schema_version":"1.0"},"canonical_sha256":"dd61c03457169dfabc2f4f1ce289ebf4845291f64443a52bccd96fb6e66a3617","source":{"kind":"arxiv","id":"1904.07528","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.07528","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.07528v1","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07528","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"pith_short_12","alias_value":"3VQ4ANCXC2O7","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"3VQ4ANCXC2O7VPBP","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"3VQ4ANCX","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3VQ4ANCXC2O7VPBPJ4OOFCPL6S","target":"record","payload":{"canonical_record":{"source":{"id":"1904.07528","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T08:15:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"968be4acd7c4762ffeb7b525fcc0906c55436769196aec10a2244ccbfdc2e9c7","abstract_canon_sha256":"649063c48b73b60a93e95cc3a0c6b37031b0667839bb7729f95356a6e6f8831f"},"schema_version":"1.0"},"canonical_sha256":"dd61c03457169dfabc2f4f1ce289ebf4845291f64443a52bccd96fb6e66a3617","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:24.968488Z","signature_b64":"Y2pa3Kd/QOf8JYJsf4/AkmxxXJSkcUogdkafbfQ5CKWW3NdVXP/Lul5x6iAuK4S0uxcZvJGDVQqZzMMsEvZJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd61c03457169dfabc2f4f1ce289ebf4845291f64443a52bccd96fb6e66a3617","last_reissued_at":"2026-05-17T23:48:24.967873Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:24.967873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.07528","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":"2026-05-17T23:48:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nb/eMCCJEj/9CiEBXkpUGQws0apyCZeY1RoykzbGX1LJubO3VIcpNc2KZ9FePNXkfwy2cLZbm4rzVY4K91mBCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T19:52:57.254092Z"},"content_sha256":"2dad52557c95820e088d3f57dfe36cf8f53819626dad2a45412ded6d458107cd","schema_version":"1.0","event_id":"sha256:2dad52557c95820e088d3f57dfe36cf8f53819626dad2a45412ded6d458107cd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3VQ4ANCXC2O7VPBPJ4OOFCPL6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Disentangling Pose from Appearance in Monochrome Hand Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chris Twigg, Lingling Tao, Xiaogang Wang, Yikang Li, Yuting Ye","submitted_at":"2019-04-16T08:15:26Z","abstract_excerpt":"Hand pose estimation from the monocular 2D image is challenging due to the variation in lighting, appearance, and background. While some success has been achieved using deep neural networks, they typically require collecting a large dataset that adequately samples all the axes of variation of hand images. It would, therefore, be useful to find a representation of hand pose which is independent of the image appearance~(like hand texture, lighting, background), so that we can synthesize unseen images by mixing pose-appearance combinations. In this paper, we present a novel technique that disenta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07528","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":""},"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":"2026-05-17T23:48:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lWeYjCcDhs2h0qiQnjrllKTQYfXMkx3T7+sQ2uN0jtKy29/2mTwVe/VmF3T8oT2xPlXDe8IFpTqxWUJ3GwA7BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T19:52:57.254768Z"},"content_sha256":"e48f9af68c84088078f28bdfa907cb6559d6a922ced4b30a22a0426ac0bed9ae","schema_version":"1.0","event_id":"sha256:e48f9af68c84088078f28bdfa907cb6559d6a922ced4b30a22a0426ac0bed9ae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/bundle.json","state_url":"https://pith.science/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/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":"2026-05-25T19:52:57Z","links":{"resolver":"https://pith.science/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S","bundle":"https://pith.science/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/bundle.json","state":"https://pith.science/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3VQ4ANCXC2O7VPBPJ4OOFCPL6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3VQ4ANCXC2O7VPBPJ4OOFCPL6S","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":"649063c48b73b60a93e95cc3a0c6b37031b0667839bb7729f95356a6e6f8831f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T08:15:26Z","title_canon_sha256":"968be4acd7c4762ffeb7b525fcc0906c55436769196aec10a2244ccbfdc2e9c7"},"schema_version":"1.0","source":{"id":"1904.07528","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.07528","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.07528v1","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07528","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"pith_short_12","alias_value":"3VQ4ANCXC2O7","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"3VQ4ANCXC2O7VPBP","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"3VQ4ANCX","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:e48f9af68c84088078f28bdfa907cb6559d6a922ced4b30a22a0426ac0bed9ae","target":"graph","created_at":"2026-05-17T23:48:24Z","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"},"paper":{"abstract_excerpt":"Hand pose estimation from the monocular 2D image is challenging due to the variation in lighting, appearance, and background. While some success has been achieved using deep neural networks, they typically require collecting a large dataset that adequately samples all the axes of variation of hand images. It would, therefore, be useful to find a representation of hand pose which is independent of the image appearance~(like hand texture, lighting, background), so that we can synthesize unseen images by mixing pose-appearance combinations. In this paper, we present a novel technique that disenta","authors_text":"Chris Twigg, Lingling Tao, Xiaogang Wang, Yikang Li, Yuting Ye","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T08:15:26Z","title":"Disentangling Pose from Appearance in Monochrome Hand Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07528","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":"sha256:2dad52557c95820e088d3f57dfe36cf8f53819626dad2a45412ded6d458107cd","target":"record","created_at":"2026-05-17T23:48:24Z","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":"649063c48b73b60a93e95cc3a0c6b37031b0667839bb7729f95356a6e6f8831f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T08:15:26Z","title_canon_sha256":"968be4acd7c4762ffeb7b525fcc0906c55436769196aec10a2244ccbfdc2e9c7"},"schema_version":"1.0","source":{"id":"1904.07528","kind":"arxiv","version":1}},"canonical_sha256":"dd61c03457169dfabc2f4f1ce289ebf4845291f64443a52bccd96fb6e66a3617","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dd61c03457169dfabc2f4f1ce289ebf4845291f64443a52bccd96fb6e66a3617","first_computed_at":"2026-05-17T23:48:24.967873Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:24.967873Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y2pa3Kd/QOf8JYJsf4/AkmxxXJSkcUogdkafbfQ5CKWW3NdVXP/Lul5x6iAuK4S0uxcZvJGDVQqZzMMsEvZJDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:24.968488Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.07528","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2dad52557c95820e088d3f57dfe36cf8f53819626dad2a45412ded6d458107cd","sha256:e48f9af68c84088078f28bdfa907cb6559d6a922ced4b30a22a0426ac0bed9ae"],"state_sha256":"015f73f22dec53593716bee2770ba2619b7c9d897b2d3bde71079d24e969b0ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qS6Hxy9A8Isfy/SnMaMTiwj8A0cOxLgO+tqMGxDsHLiwlEe99R+oPE+w702wKKjq36crHHfu8edkFtuniySpCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T19:52:57.258431Z","bundle_sha256":"041e50455b1a085b909e722004544f38339d48f5a48486976b1a55fd5c8a48b0"}}