{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:JNWGRN4TMKCRUPJHNEPFW3VV6T","short_pith_number":"pith:JNWGRN4T","canonical_record":{"source":{"id":"1901.01760","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-07T11:58:10Z","cross_cats_sorted":[],"title_canon_sha256":"38b77a65c73ef38a4a54e7d3d91d1715c1a03c3028a5b8d1a714c33386a28102","abstract_canon_sha256":"c09147b9dd123538aa8c44c7e392b014f5eb3684d22d05dcd4bae284de578c0a"},"schema_version":"1.0"},"canonical_sha256":"4b6c68b79362851a3d27691e5b6eb5f4ccb08b7292af273505939b15eddcaf94","source":{"kind":"arxiv","id":"1901.01760","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01760","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01760v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01760","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"JNWGRN4TMKCR","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JNWGRN4TMKCRUPJH","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JNWGRN4T","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:JNWGRN4TMKCRUPJHNEPFW3VV6T","target":"record","payload":{"canonical_record":{"source":{"id":"1901.01760","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-07T11:58:10Z","cross_cats_sorted":[],"title_canon_sha256":"38b77a65c73ef38a4a54e7d3d91d1715c1a03c3028a5b8d1a714c33386a28102","abstract_canon_sha256":"c09147b9dd123538aa8c44c7e392b014f5eb3684d22d05dcd4bae284de578c0a"},"schema_version":"1.0"},"canonical_sha256":"4b6c68b79362851a3d27691e5b6eb5f4ccb08b7292af273505939b15eddcaf94","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:51.306359Z","signature_b64":"jUzsdJsR4C2c1243XQE5BI/qkpOo/cuOqI/LNGwK8MP/LTYe0ysa1ZUIIEAfzD4WRZcWh2JmJHhbfuRBnpcpDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b6c68b79362851a3d27691e5b6eb5f4ccb08b7292af273505939b15eddcaf94","last_reissued_at":"2026-05-17T23:56:51.305601Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:51.305601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.01760","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/07SnAwM/O0iDyfie7bMDMjHpctgJkyzIiagl9jn0tzvinzgucsE3esWItLLJaabxDiGxJSj47KdSStjCSDQAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:07:53.050553Z"},"content_sha256":"22822e54248d8ef0aa0e1984172d753b881b08898053834a75d870485cf395ed","schema_version":"1.0","event_id":"sha256:22822e54248d8ef0aa0e1984172d753b881b08898053834a75d870485cf395ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:JNWGRN4TMKCRUPJHNEPFW3VV6T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Human Pose Estimation with Spatial Contextual Information","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Ouyang, Hong Zhang, Jiaya Jia, Ruigang Yang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen","submitted_at":"2019-01-07T11:58:10Z","abstract_excerpt":"We explore the importance of spatial contextual information in human pose estimation. Most state-of-the-art pose networks are trained in a multi-stage manner and produce several auxiliary predictions for deep supervision. With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information. Cascade prediction fusion accumulates prediction maps from previous stages to extract informative signals. The resulting maps also function as a prior to guid"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01760","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":"2026-05-17T23:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pHVJI4IKHwD8cvYGs5jmbTPUuJ/sauIkVeMzLkhIFBUM6mSxp+ZmvfSsJaYg129XQecC/eNjkxBpoUselFvJDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:07:53.051246Z"},"content_sha256":"7ecbdf64bf579b7b02e37cd79f5c1fbdf3d63e3e0694b1005d0a69ae3b807c0e","schema_version":"1.0","event_id":"sha256:7ecbdf64bf579b7b02e37cd79f5c1fbdf3d63e3e0694b1005d0a69ae3b807c0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/bundle.json","state_url":"https://pith.science/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/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":"2026-05-31T08:07:53Z","links":{"resolver":"https://pith.science/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T","bundle":"https://pith.science/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/bundle.json","state":"https://pith.science/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JNWGRN4TMKCRUPJHNEPFW3VV6T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:JNWGRN4TMKCRUPJHNEPFW3VV6T","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":"c09147b9dd123538aa8c44c7e392b014f5eb3684d22d05dcd4bae284de578c0a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-07T11:58:10Z","title_canon_sha256":"38b77a65c73ef38a4a54e7d3d91d1715c1a03c3028a5b8d1a714c33386a28102"},"schema_version":"1.0","source":{"id":"1901.01760","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.01760","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"1901.01760v1","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01760","created_at":"2026-05-17T23:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"JNWGRN4TMKCR","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JNWGRN4TMKCRUPJH","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JNWGRN4T","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:7ecbdf64bf579b7b02e37cd79f5c1fbdf3d63e3e0694b1005d0a69ae3b807c0e","target":"graph","created_at":"2026-05-17T23:56:51Z","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":"We explore the importance of spatial contextual information in human pose estimation. Most state-of-the-art pose networks are trained in a multi-stage manner and produce several auxiliary predictions for deep supervision. With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information. Cascade prediction fusion accumulates prediction maps from previous stages to extract informative signals. The resulting maps also function as a prior to guid","authors_text":"Hao Ouyang, Hong Zhang, Jiaya Jia, Ruigang Yang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-07T11:58:10Z","title":"Human Pose Estimation with Spatial Contextual Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01760","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":"sha256:22822e54248d8ef0aa0e1984172d753b881b08898053834a75d870485cf395ed","target":"record","created_at":"2026-05-17T23:56:51Z","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":"c09147b9dd123538aa8c44c7e392b014f5eb3684d22d05dcd4bae284de578c0a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-01-07T11:58:10Z","title_canon_sha256":"38b77a65c73ef38a4a54e7d3d91d1715c1a03c3028a5b8d1a714c33386a28102"},"schema_version":"1.0","source":{"id":"1901.01760","kind":"arxiv","version":1}},"canonical_sha256":"4b6c68b79362851a3d27691e5b6eb5f4ccb08b7292af273505939b15eddcaf94","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b6c68b79362851a3d27691e5b6eb5f4ccb08b7292af273505939b15eddcaf94","first_computed_at":"2026-05-17T23:56:51.305601Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:51.305601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jUzsdJsR4C2c1243XQE5BI/qkpOo/cuOqI/LNGwK8MP/LTYe0ysa1ZUIIEAfzD4WRZcWh2JmJHhbfuRBnpcpDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:51.306359Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.01760","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:22822e54248d8ef0aa0e1984172d753b881b08898053834a75d870485cf395ed","sha256:7ecbdf64bf579b7b02e37cd79f5c1fbdf3d63e3e0694b1005d0a69ae3b807c0e"],"state_sha256":"98c979055044d5735f4ed6ff53b6ba84d1cdb56cc8bf2e93fb914be3a525b626"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DPwrFtHbZySI2zyJIEXe9fu4CczdwGXCp6X/Z6If5VUrIvSd4EG3w+IXxw12rCuRgIfE1Mk9vfu4z9nTsSuMAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T08:07:53.055112Z","bundle_sha256":"551edc8b6121397226a5d3956b7314ec19ad0816f229f38d48a20c0b0d625e26"}}