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This paper presents a novel self-supervised approach to reconstruct human shape and pose from noisy point cloud data.
Maximum likelihood from incomplete data via the em algorithm
Arthur P Dempster, Nan M Laird, and Donald B Rubin · 1977
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Method for registration of 3-d shapes
Paul J Besl and Neil D McKay · 1992
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Global correspondence optimization for non-rigid registration of depth scans
Hao Li, Robert W Sumner, and Mark Pauly · 2008
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Scale-invariant heat kernel signatures for non-rigid shape recognition
Michael M Bronstein and Iasonas Kokkinos · 2010
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Rigid and articulated point registration with expectation conditional maximization
Radu Horaud, Florence Forbes, Manuel Yguel, Guillaume Dewaele, and Jian Zhang · 2010
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Unique signatures of histograms for local surface description
Federico Tombari, Samuele Salti, and Luigi Di Stefano · 2010
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The wave kernel signature: A quantum mechanical approach to shape analysis
Mathieu Aubry, Ulrich Schlickewei, and Daniel Cremers · 2011
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Model-based learning using a mixture of mixtures of gaussian and uniform distributions
Ryan P Browne, Paul D McNicholas, and Matthew D Sparling · 2011
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Blended intrinsic maps
Vladimir G Kim, Yaron Lipman, and Thomas Funkhouser · 2011
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An optimization approach to improving collections of shape maps
Andy Nguyen, Mirela Ben-Chen, Katarzyna Welnicka, Yinyu Ye, and Leonidas Guibas · 2011
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Functional maps: a flexible representation of maps between shapes
Maks Ovsjanikov, Mirela Ben-Chen, Justin Solomon, Adrian Butscher, and Leonidas Guibas · 2012
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FAUST: Dataset and evaluation for 3D mesh registration
Federica Bogo, Javier Romero, Matthew Loper, and Michael J. Black · 2014
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Mosh: Motion and shape capture from sparse markers
Matthew Loper, Naureen Mahmood, and Michael J Black · 2014
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Real-time simultaneous pose and shape estimation for articulated objects using a single depth camera
Mao Ye and Ruigang Yang · 2014
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Smpl: A skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J Black · 2015
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Keep it smpl: Automatic estimation of 3d human pose and shape from a single image
Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter Gehler, Javier Romero, and Michael J Black · 2016
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Fusion4d: Real-time performance capture of challenging scenes
Mingsong Dou, Sameh Khamis, Yury Degtyarev, Philip Davidson, Sean Ryan Fanello, Adarsh Kowdle, Sergio Orts Escolano, Christoph Rhemann, David Kim, Jonathan Taylor, et al · 2016
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Entropic metric alignment for correspondence problems
Justin Solomon, Gabriel Peyré, Vladimir G Kim, and Suvrit Sra · 2016
Earlier work this paper cites.
Dense human body correspondences using convolutional networks
Lingyu Wei, Qixing Huang, Duygu Ceylan, Etienne Vouga, and Hao Li · 2016
Cited alongside, same era.
Dynamic faust: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J Black · 2017
Cited alongside, same era.
Panoptic studio: A massively multiview system for social interaction capture
Hanbyul Joo, Tomas Simon, Xulong Li, Hao Liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart, Bart Nabbe, Iain Matthews, et al · 2017
Cited alongside, same era.
Deep functional maps: Structured prediction for dense shape correspondence
Or Litany, Tal Remez, Emanuele Rodola, Alex Bronstein, and Michael Bronstein · 2017
Cited alongside, same era.
Clothcap: Seamless 4d clothing capture and retargeting
Gerard Pons-Moll, Sergi Pujades, Sonny Hu, and Michael J Black · 2017
Cited alongside, same era.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Combining implicit function learning and parametric models for 3d human reconstruction
Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, and Gerard Pons-Moll · 2020
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Loopreg: Self-supervised learning of implicit surface correspondences, pose and shape for 3d human mesh registration
Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, and Gerard Pons-Moll · 2020
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Who left the dogs out? 3d animal reconstruction with expectation maximization in the loop
Benjamin Biggs, Oliver Boyne, James Charles, Andrew Fitzgibbon, and Roberto Cipolla · 2020
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Implicit functions in feature space for 3d shape reconstruction and completion
Julian Chibane, Thiemo Alldieck, and Gerard Pons-Moll · 2020
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Deep shells: Unsupervised shape correspondence with optimal transport
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, and Daniel Cremers · 2020
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Charles R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
Embodied hands: Modeling and capturing hands and bodies together
Javier Romero, Dimitrios Tzionas, and Michael J Black · 2017
Cited alongside, same era.
Product manifold filter: Non-rigid shape correspondence via kernel density estimation in the product space
Matthias Vestner, Roee Litman, Emanuele Rodola, Alex Bronstein, and Daniel Cremers · 2017
Cited alongside, same era.
3d-coded: 3d correspondences by deep deformation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
Cited alongside, same era.
Doublefusion: Real-time capture of human performances with inner body shapes from a single depth sensor
Tao Yu, Zerong Zheng, Kaiwen Guo, Jianhui Zhao, Qionghai Dai, Hao Li, Gerard Pons-Moll, and Yebin Liu · 2018
Cited alongside, same era.
Skeleton-aware 3d human shape reconstruction from point clouds
Haiyong Jiang, Jianfei Cai, and Jianmin Zheng · 2019
Cited alongside, same era.
Learning to reconstruct 3d human pose and shape via model-fitting in the loop
Nikos Kolotouros, Georgios Pavlakos, Michael J Black, and Kostas Daniilidis · 2019
Cited alongside, same era.
Cyclic functional mapping: Self-supervised correspondence between non-isometric deformable shapes
Dvir Ginzburg and Dan Raviv · 2020
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Learning to dress 3d people in generative clothing
Qianli Ma, Jinlong Yang, Anurag Ranjan, Sergi Pujades, Gerard Pons-Moll, Siyu Tang, and Michael J Black · 2020
Later among the works it cites.
Farm: Functional automatic registration method for 3d human bodies
Riccardo Marin, Simone Melzi, Emanuele Rodola, and Umberto Castellani · 2020
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Sequential 3d human pose and shape estimation from point clouds
Kangkan Wang, Jin Xie, Guofeng Zhang, Lei Liu, and Jian Yang · 2020
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Recurrent multi-view alignment network for unsupervised surface registration
Wanquan Feng, Juyong Zhang, Hongrui Cai, Haofei Xu, Junhui Hou, and Hujun Bao · 2021
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Posefusion: Pose-guided selective fusion for single-view human volumetric capture
Zhe Li, Tao Yu, Zerong Zheng, Kaiwen Guo, and Yebin Liu · 2021
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Scale: Modeling clothed humans with a surface codec of articulated local elements
Qianli Ma, Shunsuke Saito, Jinlong Yang, Siyu Tang, and Michael J Black · 2021
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The power of points for modeling humans in clothing
Qianli Ma, Jinlong Yang, Siyu Tang, and Michael J Black · 2021
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Leap: Learning articulated occupancy of people
Marko Mihajlovic, Yan Zhang, Michael J Black, and Siyu Tang · 2021
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Scanimate: Weakly supervised learning of skinned clothed avatar networks
Shunsuke Saito, Jinlong Yang, Qianli Ma, and Michael J Black · 2021
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Learning dense correspondences for non-rigid point clouds with two-stage regression
Kangkan Wang, Guofeng Zhang, Huayu Zheng, and Jian Yang · 2021
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Locally aware piecewise transformation fields for 3d human mesh registration
Shaofei Wang, Andreas Geiger, and Siyu Tang · 2021
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