{"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/densepose-dense-human-pose-estimation-in-the","title":"DensePose: Dense Human Pose Estimation In The Wild","arxiv_id":"1802.00434","date":"2018-02-01","proceeding":"CVPR 2018 6","authors":["Riza Alp Güler","Natalia Neverova","Iasonas Kokkinos"],"abstract":"In this work, we establish dense correspondences between RGB image and a\nsurface-based representation of the human body, a task we refer to as dense\nhuman pose estimation. We first gather dense correspondences for 50K persons\nappearing in the COCO dataset by introducing an efficient annotation pipeline.\nWe then use our dataset to train CNN-based systems that deliver dense\ncorrespondence 'in the wild', namely in the presence of background, occlusions\nand scale variations. We improve our training set's effectiveness by training\nan 'inpainting' network that can fill in missing groundtruth values and report\nclear improvements with respect to the best results that would be achievable in\nthe past. We experiment with fully-convolutional networks and region-based\nmodels and observe a superiority of the latter; we further improve accuracy\nthrough cascading, obtaining a system that delivers highly0accurate results in\nreal time. Supplementary materials and videos are provided on the project page\nhttp://densepose.org","url_abs":"http://arxiv.org/abs/1802.00434v1","url_pdf":"http://arxiv.org/pdf/1802.00434v1.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":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/ARMUGHAN-SHAHID/MoboDensepose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/AkashGanesan/PedestrianAttention","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/M-Usman10/DenseSqueeze-RCNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/StupidmanTan/facebookresearch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/UBC-Computer-Vision-Group/DwNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/chengjiali/DensePose3","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/chuanqichen/deepcoaching","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/dajes/DensePose-TorchScript","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/facebookresearch/DensePose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/facebookresearch/detectron","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/facebookresearch/detectron2/tree/master/projects/DensePose/","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/freedombenLiu/DensePose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/hz-ants/DensePose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/jarrodanderson/densepose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/jiajunhua/facebookresearch-DensePose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/jiajunhua/facebookresearch-Detectron","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":null},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/lncarter/Dencepose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/sgoldyaev/DeepFashion.ADGAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/stimong/DensePose_python3","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/svikramank/DensePose","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"caffe2","reach":{"status":"unanswered"}},{"paper_slug":"densepose-dense-human-pose-estimation-in-the","repo_url":"https://github.com/ubc-vision/DwNet","is_official":0,"mentioned_in_paper":0,"mentione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Human Pose Estimation"},{"task_slug":"monocular-3d-human-pose-estimation","task_name":"Monocular 3D Human Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"mask-r-cnn","method_name":"Mask R-CNN"},{"method_slug":"rpn","method_name":"RPN"},{"method_slug":"roi-align","method_name":"RoIAlign"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[{"slug":"densepose","name":"DensePose","full_name":"DensePose-COCO"}],"methods_introduced":[],"results":[{"leaderboard":"/sota/pose-estimation-on-densepose-coco","task":"Pose Estimation","dataset":"DensePose-COCO","model":"DensePose + keypoints","rank_in_archive_order":3,"of":4,"metrics":{"AP":"55.8"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1802.00434","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}