{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:O7WA2NLN6TYGT2D4I6KNIFBSWC","short_pith_number":"pith:O7WA2NLN","canonical_record":{"source":{"id":"1404.4923","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-19T04:51:06Z","cross_cats_sorted":[],"title_canon_sha256":"d04f5f5ccae0ba567c28044307b90513f2b24fc7150d080a48baecb8d767ba4a","abstract_canon_sha256":"33c2d9a30f88544e24d49da6d47fbf48e7ce174d73c6a2f901b33c75345eeabe"},"schema_version":"1.0"},"canonical_sha256":"77ec0d356df4f069e87c4794d41432b0ad7ee57b029e7c89a2bdc7d5afe4e900","source":{"kind":"arxiv","id":"1404.4923","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.4923","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"arxiv_version","alias_value":"1404.4923v3","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.4923","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"pith_short_12","alias_value":"O7WA2NLN6TYG","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"O7WA2NLN6TYGT2D4","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"O7WA2NLN","created_at":"2026-05-18T12:28:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:O7WA2NLN6TYGT2D4I6KNIFBSWC","target":"record","payload":{"canonical_record":{"source":{"id":"1404.4923","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-19T04:51:06Z","cross_cats_sorted":[],"title_canon_sha256":"d04f5f5ccae0ba567c28044307b90513f2b24fc7150d080a48baecb8d767ba4a","abstract_canon_sha256":"33c2d9a30f88544e24d49da6d47fbf48e7ce174d73c6a2f901b33c75345eeabe"},"schema_version":"1.0"},"canonical_sha256":"77ec0d356df4f069e87c4794d41432b0ad7ee57b029e7c89a2bdc7d5afe4e900","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:43:27.307460Z","signature_b64":"a1u8sSlqsCFBnjhzruwA4KS608slw7RABii1kia2WBxngBzKfet2FbsBVlPXjnTaZLmk7vu35znnzv6cX8COBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"77ec0d356df4f069e87c4794d41432b0ad7ee57b029e7c89a2bdc7d5afe4e900","last_reissued_at":"2026-05-18T01:43:27.306806Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:43:27.306806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1404.4923","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":"2026-05-18T01:43:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WR1rXlJTppezOaLzV9NJAWqRj+G5Og5jOu4/ENymCN9Cg1yKSjcHw8fPq+kvdmQeCdqjDhxHgm5cJqzvCMmhCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T10:25:37.467291Z"},"content_sha256":"d9b3ea98755e8468e9ef1fa01f72683ee563ef14e9de2e6841e1e2d79c89625b","schema_version":"1.0","event_id":"sha256:d9b3ea98755e8468e9ef1fa01f72683ee563ef14e9de2e6841e1e2d79c89625b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:O7WA2NLN6TYGT2D4I6KNIFBSWC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unified Structured Learning for Simultaneous Human Pose Estimation and Garment Attribute Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guangcan Liu, Jia Chen, Jianbin Xie, Jie Shen, Shuicheng Yan, Yong Yu, Yuqiang Fang","submitted_at":"2014-04-19T04:51:06Z","abstract_excerpt":"In this paper, we utilize structured learning to simultaneously address two intertwined problems: human pose estimation (HPE) and garment attribute classification (GAC), which are valuable for a variety of computer vision and multimedia applications. Unlike previous works that usually handle the two problems separately, our approach aims to produce a jointly optimal estimation for both HPE and GAC via a unified inference procedure. To this end, we adopt a preprocessing step to detect potential human parts from each image (i.e., a set of \"candidates\") that allows us to have a manageable input s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.4923","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":"2026-05-18T01:43:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XIqmEOda1SSIertc5kZ2GscjVBum1Ou+49J7MgII/BJISrtsPVCb5evN9m81qM0n5yTI3blaPd/uWJDBV6g6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T10:25:37.467658Z"},"content_sha256":"bb2611f68aaa2fec0408b00af7ed586f76a5971c5c6ab010d0799c5a605647ea","schema_version":"1.0","event_id":"sha256:bb2611f68aaa2fec0408b00af7ed586f76a5971c5c6ab010d0799c5a605647ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/bundle.json","state_url":"https://pith.science/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/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":"2026-05-21T10:25:37Z","links":{"resolver":"https://pith.science/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC","bundle":"https://pith.science/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/bundle.json","state":"https://pith.science/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/O7WA2NLN6TYGT2D4I6KNIFBSWC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:O7WA2NLN6TYGT2D4I6KNIFBSWC","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":"33c2d9a30f88544e24d49da6d47fbf48e7ce174d73c6a2f901b33c75345eeabe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-19T04:51:06Z","title_canon_sha256":"d04f5f5ccae0ba567c28044307b90513f2b24fc7150d080a48baecb8d767ba4a"},"schema_version":"1.0","source":{"id":"1404.4923","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1404.4923","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"arxiv_version","alias_value":"1404.4923v3","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.4923","created_at":"2026-05-18T01:43:27Z"},{"alias_kind":"pith_short_12","alias_value":"O7WA2NLN6TYG","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"O7WA2NLN6TYGT2D4","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"O7WA2NLN","created_at":"2026-05-18T12:28:41Z"}],"graph_snapshots":[{"event_id":"sha256:bb2611f68aaa2fec0408b00af7ed586f76a5971c5c6ab010d0799c5a605647ea","target":"graph","created_at":"2026-05-18T01:43:27Z","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":"In this paper, we utilize structured learning to simultaneously address two intertwined problems: human pose estimation (HPE) and garment attribute classification (GAC), which are valuable for a variety of computer vision and multimedia applications. Unlike previous works that usually handle the two problems separately, our approach aims to produce a jointly optimal estimation for both HPE and GAC via a unified inference procedure. To this end, we adopt a preprocessing step to detect potential human parts from each image (i.e., a set of \"candidates\") that allows us to have a manageable input s","authors_text":"Guangcan Liu, Jia Chen, Jianbin Xie, Jie Shen, Shuicheng Yan, Yong Yu, Yuqiang Fang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-19T04:51:06Z","title":"Unified Structured Learning for Simultaneous Human Pose Estimation and Garment Attribute Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.4923","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:d9b3ea98755e8468e9ef1fa01f72683ee563ef14e9de2e6841e1e2d79c89625b","target":"record","created_at":"2026-05-18T01:43:27Z","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":"33c2d9a30f88544e24d49da6d47fbf48e7ce174d73c6a2f901b33c75345eeabe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-04-19T04:51:06Z","title_canon_sha256":"d04f5f5ccae0ba567c28044307b90513f2b24fc7150d080a48baecb8d767ba4a"},"schema_version":"1.0","source":{"id":"1404.4923","kind":"arxiv","version":3}},"canonical_sha256":"77ec0d356df4f069e87c4794d41432b0ad7ee57b029e7c89a2bdc7d5afe4e900","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77ec0d356df4f069e87c4794d41432b0ad7ee57b029e7c89a2bdc7d5afe4e900","first_computed_at":"2026-05-18T01:43:27.306806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:43:27.306806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"a1u8sSlqsCFBnjhzruwA4KS608slw7RABii1kia2WBxngBzKfet2FbsBVlPXjnTaZLmk7vu35znnzv6cX8COBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:43:27.307460Z","signed_message":"canonical_sha256_bytes"},"source_id":"1404.4923","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9b3ea98755e8468e9ef1fa01f72683ee563ef14e9de2e6841e1e2d79c89625b","sha256:bb2611f68aaa2fec0408b00af7ed586f76a5971c5c6ab010d0799c5a605647ea"],"state_sha256":"19d8ea5484aff802509853d2b06244ce909959535b1015d034d595a0696a4884"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C+bmTEq+Il60HlOFHxiwyKmagIGD7wbR6qI8KF3QM+nmC9KuB2AO8LtdluBWSobmCyUu0F1YBb/w9pOFcPaqAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T10:25:37.469655Z","bundle_sha256":"338fbb330eac1fc786477715a2b004e5ba8da90919dfdae656fd342e81a41add"}}