{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/distribution-aware-single-stage-models-for","title":"Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation","arxiv_id":"2203.07697","date":"2022-03-15","proceeding":"CVPR 2022 1","authors":["Zitian Wang","Xuecheng Nie","Xiaochao Qu","Yunpeng Chen","Si Liu"],"abstract":"In this paper, we present a novel Distribution-Aware Single-stage (DAS) model for tackling the challenging multi-person 3D pose estimation problem. Different from existing top-down and bottom-up methods, the proposed DAS model simultaneously localizes person positions and their corresponding body joints in the 3D camera space in a one-pass manner. This leads to a simplified pipeline with enhanced efficiency. In addition, DAS learns the true distribution of body joints for the regression of their positions, rather than making a simple Laplacian or Gaussian assumption as previous works. This provides valuable priors for model prediction and thus boosts the regression-based scheme to achieve competitive performance with volumetric-base ones. Moreover, DAS exploits a recursive update strategy for progressively approaching to regression target, alleviating the optimization difficulty and further lifting the regression performance. DAS is implemented with a fully Convolutional Neural Network and end-to-end learnable. Comprehensive experiments on benchmarks CMU Panoptic and MuPoTS-3D demonstrate the superior efficiency of the proposed DAS model, specifically 1.5x speedup over previous best model, and its stat-of-the-art accuracy for multi-person 3D pose estimation.","url_abs":"https://arxiv.org/abs/2203.07697v4","url_pdf":"https://arxiv.org/pdf/2203.07697v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"distribution-aware-single-stage-models-for","repo_url":"https://github.com/wangzt-halo/das","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"3d-multi-person-pose-estimation","task_name":"3D Multi-Person Pose Estimation"},{"task_slug":"3d-multi-person-pose-estimation-absolute","task_name":"3D Multi-Person Pose Estimation (absolute)"},{"task_slug":"3d-multi-person-pose-estimation-root-relative","task_name":"3D Multi-Person Pose Estimation (root-relative)"},{"task_slug":"3d-pose-estimation","task_name":"3D Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/3d-multi-person-pose-estimation-on-cmu","task":"3D Multi-Person Pose Estimation","dataset":"Panoptic","model":"DAS","rank_in_archive_order":15,"of":20,"metrics":{"Average MPJPE (mm)":"53.8"},"uses_additional_data":true},{"leaderboard":"/sota/3d-multi-person-pose-estimation-absolute-on","task":"3D Multi-Person Pose Estimation (absolute)","dataset":"MuPoTS-3D","model":"DAS","rank_in_archive_order":8,"of":14,"metrics":{"3DPCK":" 39.2"},"uses_additional_data":false},{"leaderboard":"/sota/3d-multi-person-pose-estimation-root-relative","task":"3D Multi-Person Pose Estimation (root-relative)","dataset":"MuPoTS-3D","model":"DAS","rank_in_archive_order":11,"of":20,"metrics":{"3DPCK":"82.7"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2203.07697","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.07697"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/wangzt-halo/das","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":1,"unverified":2},"by_repo_kind":{"listed":{"samples":3,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"e76a491553cf9fcf","entry":"process_checkpoint","repo":"wangzt-halo/das","repo_kind":"listed","path":".dev_scripts/gather_models.py","file_url":"https://github.com/wangzt-halo/das/blob/HEAD/.dev_scripts/gather_models.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e76a491553cf9fcf"}},{"code_sha256_prefix":"90f6ae7209cde36f","entry":"get_final_epoch","repo":"wangzt-halo/das","repo_kind":"listed","path":".dev_scripts/gather_models.py","file_url":"https://github.com/wangzt-halo/das/blob/HEAD/.dev_scripts/gather_models.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"90f6ae7209cde36f"}},{"code_sha256_prefix":"da059252c88ecf40","entry":"get_model_dataset","repo":"wangzt-halo/das","repo_kind":"listed","path":".dev_scripts/gather_models.py","file_url":"https://github.com/wangzt-halo/das/blob/HEAD/.dev_scripts/gather_models.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"da059252c88ecf40"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}