{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AZ2BEZI3THUCIXHP6KYEKC4MZA","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":"5ef49d809e0e246f5bcf8220926b104d33811408511439321e013ebb302b07dd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-20T10:47:46Z","title_canon_sha256":"d880ba85aed616ebed3d2bcaae288a4316ef3e95585357613eb769ae6b4fc0a3"},"schema_version":"1.0","source":{"id":"1908.07919","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.07919","created_at":"2026-07-05T00:47:38Z"},{"alias_kind":"arxiv_version","alias_value":"1908.07919v2","created_at":"2026-07-05T00:47:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.07919","created_at":"2026-07-05T00:47:38Z"},{"alias_kind":"pith_short_12","alias_value":"AZ2BEZI3THUC","created_at":"2026-07-05T00:47:38Z"},{"alias_kind":"pith_short_16","alias_value":"AZ2BEZI3THUCIXHP","created_at":"2026-07-05T00:47:38Z"},{"alias_kind":"pith_short_8","alias_value":"AZ2BEZI3","created_at":"2026-07-05T00:47:38Z"}],"graph_snapshots":[{"event_id":"sha256:4ed9701821390cef386d762466625db105928e3918a5c8b7328abcdfe0526d80","target":"graph","created_at":"2026-07-05T00:47:38Z","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/1908.07919/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-the-art frameworks first encode the input image as a low-resolution representation through a subnetwork that is formed by connecting high-to-low resolution convolutions \\emph{in series} (e.g., ResNet, VGGNet), and then recover the high-resolution representation from the encoded low-resolution representation. Instead, our proposed network, named as High-Resolution Network (HRNet), maintains high-resolution representat","authors_text":"Bin Xiao, Borui Jiang, Chaorui Deng, Dong Liu, Jingdong Wang, Ke Sun, Mingkui Tan, Tianheng Cheng, Wenyu Liu, Xinggang Wang, Yadong Mu, Yang Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-20T10:47:46Z","title":"Deep High-Resolution Representation Learning for Visual Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.07919","kind":"arxiv","version":2},"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":"sha256:75d6390f81d77d35bb0be162048e969fc259d6d8453f09774ec1fca544202610","target":"record","created_at":"2026-07-05T00:47:38Z","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":"5ef49d809e0e246f5bcf8220926b104d33811408511439321e013ebb302b07dd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-20T10:47:46Z","title_canon_sha256":"d880ba85aed616ebed3d2bcaae288a4316ef3e95585357613eb769ae6b4fc0a3"},"schema_version":"1.0","source":{"id":"1908.07919","kind":"arxiv","version":2}},"canonical_sha256":"067412651b99e8245ceff2b0450b8cc80816bfc6ecb5a5e38f8270dc693eea77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"067412651b99e8245ceff2b0450b8cc80816bfc6ecb5a5e38f8270dc693eea77","first_computed_at":"2026-07-05T00:47:38.177103Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:47:38.177103Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GTCS+bnyiVAz4Y1TJIeozNrxOQg09o9lDXGGjMpwOM24jVgPCl7CQ6XJL/WxC5f6wk4rlra4Q+JPsidV3J1PAg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:47:38.177603Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.07919","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75d6390f81d77d35bb0be162048e969fc259d6d8453f09774ec1fca544202610","sha256:4ed9701821390cef386d762466625db105928e3918a5c8b7328abcdfe0526d80"],"state_sha256":"089f928fd1092b07db23b059a9b199e37226000723a1354ce9a9aeae082e38ab"}