{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:IOX7YTJBFPMG4EFX6XFYKGX3E6","short_pith_number":"pith:IOX7YTJB","canonical_record":{"source":{"id":"1704.00159","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-04-01T11:59:41Z","cross_cats_sorted":[],"title_canon_sha256":"e493cc5485a1b54341b07a9dfb5a655ca63a7ebabe75f96417f927bd104b860d","abstract_canon_sha256":"651933844c0d4267d7c9a790a3fe2ce84fdb47a92e3ca48aca40cf859bc3c92b"},"schema_version":"1.0"},"canonical_sha256":"43affc4d212bd86e10b7f5cb851afb278f4fb80dc4866fb39cceec815f1c5def","source":{"kind":"arxiv","id":"1704.00159","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.00159","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"arxiv_version","alias_value":"1704.00159v3","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.00159","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"pith_short_12","alias_value":"IOX7YTJBFPMG","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"IOX7YTJBFPMG4EFX","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"IOX7YTJB","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:IOX7YTJBFPMG4EFX6XFYKGX3E6","target":"record","payload":{"canonical_record":{"source":{"id":"1704.00159","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-04-01T11:59:41Z","cross_cats_sorted":[],"title_canon_sha256":"e493cc5485a1b54341b07a9dfb5a655ca63a7ebabe75f96417f927bd104b860d","abstract_canon_sha256":"651933844c0d4267d7c9a790a3fe2ce84fdb47a92e3ca48aca40cf859bc3c92b"},"schema_version":"1.0"},"canonical_sha256":"43affc4d212bd86e10b7f5cb851afb278f4fb80dc4866fb39cceec815f1c5def","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:46.065337Z","signature_b64":"Cm7x/Fcw7+gF40qy7JT+ty26l2pTf7gX0JTXuizpDihAAMvsDli0VTwX8YYouJjL/S/Q0PioNhMhieU5KzF2Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43affc4d212bd86e10b7f5cb851afb278f4fb80dc4866fb39cceec815f1c5def","last_reissued_at":"2026-05-18T00:38:46.064709Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:46.064709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.00159","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:38:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"m0eYK8prcxyJruPbGcFMhW5gnt30hwKH7pysnAADbGbKFCuSkljvJk/RRJEQXrbVivI8VzpSDBROoNQZTF5qDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T01:31:41.553572Z"},"content_sha256":"3bf117acf1d65b66d184ab53213371a551c3e48a2e0922c6289b1a67cfc72312","schema_version":"1.0","event_id":"sha256:3bf117acf1d65b66d184ab53213371a551c3e48a2e0922c6289b1a67cfc72312"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:IOX7YTJBFPMG4EFX6XFYKGX3E6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Compositional Human Pose Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiaxiang Shang, Shuang Liang, Xiao Sun, Yichen Wei","submitted_at":"2017-04-01T11:59:41Z","abstract_excerpt":"Regression based methods are not performing as well as detection based methods for human pose estimation. A central problem is that the structural information in the pose is not well exploited in the previous regression methods. In this work, we propose a structure-aware regression approach. It adopts a reparameterized pose representation using bones instead of joints. It exploits the joint connection structure to define a compositional loss function that encodes the long range interactions in the pose. It is simple, effective, and general for both 2D and 3D pose estimation in a unified settin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.00159","kind":"arxiv","version":3},"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":"2026-05-18T00:38:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aoreiZUln7E70lBKODaA0rg5b+BfVHv8mXmMhROnbFFD+d5eZbwRr+1dj4qjv/wYYJrRkgi09wL/bMEBu5fWBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T01:31:41.554013Z"},"content_sha256":"f31fcc7b7218de7a6ed0ada68ac361135e176365aca76b4895fd69efbea86f82","schema_version":"1.0","event_id":"sha256:f31fcc7b7218de7a6ed0ada68ac361135e176365aca76b4895fd69efbea86f82"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/bundle.json","state_url":"https://pith.science/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/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":"2026-05-23T01:31:41Z","links":{"resolver":"https://pith.science/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6","bundle":"https://pith.science/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/bundle.json","state":"https://pith.science/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IOX7YTJBFPMG4EFX6XFYKGX3E6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:IOX7YTJBFPMG4EFX6XFYKGX3E6","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":"651933844c0d4267d7c9a790a3fe2ce84fdb47a92e3ca48aca40cf859bc3c92b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-04-01T11:59:41Z","title_canon_sha256":"e493cc5485a1b54341b07a9dfb5a655ca63a7ebabe75f96417f927bd104b860d"},"schema_version":"1.0","source":{"id":"1704.00159","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.00159","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"arxiv_version","alias_value":"1704.00159v3","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.00159","created_at":"2026-05-18T00:38:46Z"},{"alias_kind":"pith_short_12","alias_value":"IOX7YTJBFPMG","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"IOX7YTJBFPMG4EFX","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"IOX7YTJB","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:f31fcc7b7218de7a6ed0ada68ac361135e176365aca76b4895fd69efbea86f82","target":"graph","created_at":"2026-05-18T00:38:46Z","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"},"paper":{"abstract_excerpt":"Regression based methods are not performing as well as detection based methods for human pose estimation. A central problem is that the structural information in the pose is not well exploited in the previous regression methods. In this work, we propose a structure-aware regression approach. It adopts a reparameterized pose representation using bones instead of joints. It exploits the joint connection structure to define a compositional loss function that encodes the long range interactions in the pose. It is simple, effective, and general for both 2D and 3D pose estimation in a unified settin","authors_text":"Jiaxiang Shang, Shuang Liang, Xiao Sun, Yichen Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-04-01T11:59:41Z","title":"Compositional Human Pose Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.00159","kind":"arxiv","version":3},"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":"sha256:3bf117acf1d65b66d184ab53213371a551c3e48a2e0922c6289b1a67cfc72312","target":"record","created_at":"2026-05-18T00:38:46Z","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":"651933844c0d4267d7c9a790a3fe2ce84fdb47a92e3ca48aca40cf859bc3c92b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-04-01T11:59:41Z","title_canon_sha256":"e493cc5485a1b54341b07a9dfb5a655ca63a7ebabe75f96417f927bd104b860d"},"schema_version":"1.0","source":{"id":"1704.00159","kind":"arxiv","version":3}},"canonical_sha256":"43affc4d212bd86e10b7f5cb851afb278f4fb80dc4866fb39cceec815f1c5def","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"43affc4d212bd86e10b7f5cb851afb278f4fb80dc4866fb39cceec815f1c5def","first_computed_at":"2026-05-18T00:38:46.064709Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:46.064709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Cm7x/Fcw7+gF40qy7JT+ty26l2pTf7gX0JTXuizpDihAAMvsDli0VTwX8YYouJjL/S/Q0PioNhMhieU5KzF2Cw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:46.065337Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.00159","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3bf117acf1d65b66d184ab53213371a551c3e48a2e0922c6289b1a67cfc72312","sha256:f31fcc7b7218de7a6ed0ada68ac361135e176365aca76b4895fd69efbea86f82"],"state_sha256":"e0515dd129b491afadd232dc7c699296bbd4cde9958da3d0fdcc489efe5e999d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LT0uPKfot/JIsarmhpjI8E1TaVVLPsBYgl6U57LDWiTRZ1IamoQ/83GFMeGvxLpEO1j5HdU3mTVWYZYWj3bzDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T01:31:41.556277Z","bundle_sha256":"6c8da2937bc405498f90c513c53119c6dba76a937aa1aef80587ce4830d60d21"}}