{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:CQ5JQOFSFZ3B2SI5GNKBIOXSVJ","short_pith_number":"pith:CQ5JQOFS","schema_version":"1.0","canonical_sha256":"143a9838b22e761d491d3354143af2aa70a2de554fdeba45869ce3c06a37e4f3","source":{"kind":"arxiv","id":"2006.15576","version":2},"attestation_state":"computed","paper":{"title":"SMPR: Single-Stage Multi-Person Pose Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huixin Miao, Junjie Cao, Junqi Lin, Risheng Liu, Zhixun Su","submitted_at":"2020-06-28T11:26:38Z","abstract_excerpt":"Existing multi-person pose estimators can be roughly divided into two-stage approaches (top-down and bottom-up approaches) and one-stage approaches. The two-stage methods either suffer high computational redundancy for additional person detectors or group keypoints heuristically after predicting all the instance-free keypoints. The recently proposed single-stage methods do not rely on the above two extra stages but have lower performance than the latest bottom-up approaches. In this work, a novel single-stage multi-person pose regression, termed SMPR, is presented. It follows the paradigm of d"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2006.15576","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-28T11:26:38Z","cross_cats_sorted":[],"title_canon_sha256":"50a05cafae0a42b8dbddde7c14d9feda5d253f64d0c63a25f5a7ce536bbda9d3","abstract_canon_sha256":"c9bd43894d6dcef06631bba7376570c265285199c25a1b1f8801249dd2f565af"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:55:11.021579Z","signature_b64":"tPFsinKRqAxPvEDFWj5+xohOTlf6fET3MNd1D/uVKiscZEnNSsIz2c1KserSpvNYkNxdcZr5QLx4Vu1qWcPSCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"143a9838b22e761d491d3354143af2aa70a2de554fdeba45869ce3c06a37e4f3","last_reissued_at":"2026-07-05T01:55:11.021121Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:55:11.021121Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SMPR: Single-Stage Multi-Person Pose Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huixin Miao, Junjie Cao, Junqi Lin, Risheng Liu, Zhixun Su","submitted_at":"2020-06-28T11:26:38Z","abstract_excerpt":"Existing multi-person pose estimators can be roughly divided into two-stage approaches (top-down and bottom-up approaches) and one-stage approaches. The two-stage methods either suffer high computational redundancy for additional person detectors or group keypoints heuristically after predicting all the instance-free keypoints. The recently proposed single-stage methods do not rely on the above two extra stages but have lower performance than the latest bottom-up approaches. In this work, a novel single-stage multi-person pose regression, termed SMPR, is presented. It follows the paradigm of d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.15576","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2006.15576/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2006.15576","created_at":"2026-07-05T01:55:11.021178+00:00"},{"alias_kind":"arxiv_version","alias_value":"2006.15576v2","created_at":"2026-07-05T01:55:11.021178+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.15576","created_at":"2026-07-05T01:55:11.021178+00:00"},{"alias_kind":"pith_short_12","alias_value":"CQ5JQOFSFZ3B","created_at":"2026-07-05T01:55:11.021178+00:00"},{"alias_kind":"pith_short_16","alias_value":"CQ5JQOFSFZ3B2SI5","created_at":"2026-07-05T01:55:11.021178+00:00"},{"alias_kind":"pith_short_8","alias_value":"CQ5JQOFS","created_at":"2026-07-05T01:55:11.021178+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ","json":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ.json","graph_json":"https://pith.science/api/pith-number/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/graph.json","events_json":"https://pith.science/api/pith-number/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/events.json","paper":"https://pith.science/paper/CQ5JQOFS"},"agent_actions":{"view_html":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ","download_json":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ.json","view_paper":"https://pith.science/paper/CQ5JQOFS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2006.15576&json=true","fetch_graph":"https://pith.science/api/pith-number/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/graph.json","fetch_events":"https://pith.science/api/pith-number/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/action/storage_attestation","attest_author":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/action/author_attestation","sign_citation":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/action/citation_signature","submit_replication":"https://pith.science/pith/CQ5JQOFSFZ3B2SI5GNKBIOXSVJ/action/replication_record"}},"created_at":"2026-07-05T01:55:11.021178+00:00","updated_at":"2026-07-05T01:55:11.021178+00:00"}