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We introduce MotioNet, a deep neural network that directly reconstructs the motion of a 3D human skeleton from monocular video.While previous methods rely on either rigging or inverse kinematics (IK) to associate a consistent skeleton with temporally coherent joint rotations, our method is the first data-driven approach that directly outputs a kinematic skeleton, which is a complete, commonly used, motion representation.
XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera
Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller, Weipeng Xu, Mohamed Elgharib, Pascal Fua, Hans-Peter Seidel, Helge Rhodin, Gerard Pons-Moll, and Christian Theobalt. 2019 · 1907
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Gravity as a Reference for Estimating a Person’s Height from Video
Didier Bieler, Semih Günel, Pascal Fua, and Helge Rhodin. 2019 · 1909
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DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare
Yuanlu Xu, Song-Chun Zhu, and Tony Tung. 2019 · 1910
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Reconstructing 3D Human Pose from 2D Image Landmarks. In Proceedings of the European Conference on Computer Vision (ECCV ’12) , Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, and Cordelia Schmid (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 573–586
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Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments
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Markerless Motion Capture of Multiple Characters Using Multiview Image Segmentation
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Real-Time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera. In Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’14) . IEEE Computer Society, Washington, DC, USA, 2353–2360
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SMPL: A Skinned Multi-person Linear Model
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Pose-Conditioned Joint Angle Limits for 3D Human Pose Reconstruction. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’15) . IEEE Computer Society, Washington, DC, USA
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Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image. In Proceedings of the European Conference on Computer Vision (ECCV ’16) . Springer, Berlin, Germany, 561–578
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3D Human Pose Estimation via Deep Learning from 2D Annotations. In 2016 Fourth International Conference on 3D Vision (3DV’ 16) . 582–591
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Human Pose Estimation with Iterative Error Feedback. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’16) . IEEE Computer Society, Washington, DC, USA, 4733–4742
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Stacked Hourglass Networks for Human Pose Estimation. In Proceedings of the European Conference on Computer Vision (ECCV ’18)
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3D Human Pose Estimation: A Review of the Literature and Analysis of Covariates
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Direct prediction of 3d body poses from motion compensated sequences. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’16) . IEEE Computer Society, Washington, DC, USA, 991–1000
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Convolutional Pose Machines. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’16) . IEEE Computer Society, Washington, DC, USA, 4724–4732
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Deep kinematic pose regression. In Proceedings of the European Conference on Computer Vision (ECCV ’16) . Springer International Publishing, 186–201
Xingyi Zhou, Xiao Sun, Wei Zhang, Shuang Liang, and Yichen Wei. 2016 · 2016
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3d human pose estimation= 2d pose estimation+ matching. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’17) . IEEE Computer Society, Washington, DC, USA, 7035–7043
Ching-Hang Chen and Deva Ramanan. 2017 · 2017
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Adult2Child: Dynamic Scaling Laws to Create Child-like Motion. In Proceedings of the Tenth International Conference on Motion in Games (MIG ’17) . ACM, New York, NY, USA, Article 13, 13:1–13:10 pages
Yuzhu Dong, Aishat Aloba, Sachin Paryani, Lisa Anthony, Neha Rana, and Eakta Jain. 2017 · 2017
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Learning latent representations of 3d human pose with deep neural networks
Isinsu Katircioglu, Bugra Tekin, Mathieu Salzmann, Vincent Lepetit, and Pascal Fua. 2018 · 2018
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2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’18) . IEEE Computer Society, Washington, DC, USA, 5137–5146
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Learning to Estimate 3D Human Pose and Shape from a Single Color Image. In Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’18) . IEEE Computer Society, Washington, DC, USA
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Mask r-cnn. In Proceedings of the IEEE international conference on computer vision . 2961–2969
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick. 2017 · 2017
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Towards accurate marker-less human shape and pose estimation over time. In 2017 International Conference on 3D Vision (3DV) . IEEE, 421–430
Yinghao Huang, Federica Bogo, Christoph Lassner, Angjoo Kanazawa, Peter V Gehler, Javier Romero, Ijaz Akhter, and Michael J Black. 2017 · 2017
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Unite the People: Closing the Loop Between 3D and 2D Human Representations. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’17) . IEEE Computer Society, Washington, DC, USA, 4704–4713
Christoph Lassner, Javier Romero, Martin Kiefel, Federica Bogo, Michael J. Black, and Peter V. Gehler. 2017 · 2017
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Recurrent 3d pose sequence machines. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’17) . IEEE Computer Society, Washington, DC, USA, 810–819
Mude Lin, Liang Lin, Xiaodan Liang, Keze Wang, and Hui Cheng. 2017 · 2017
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A Simple Yet Effective Baseline for 3d Human Pose Estimation. In Proceeding of the IEEE International Conference on Computer Vision (ICCV ’17) . 2659–2668
Julieta Martinez, Rayat Hossain, Javier Romero, and James J. Little. 2017 · 2017
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Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision. In 2017 Fifth International Conference on 3D Vision (3DV’ 17) . IEEE Computer Society, 506–516
Dushyant Mehta, Helge Rhodin, Dan Casas, Pascal Fua, Oleksandr Sotnychenko, Weipeng Xu, and Christian Theobalt. 2017a · 2017
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VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
Dushyant Mehta, Srinath Sridhar, Oleksandr Sotnychenko, Helge Rhodin, Mohammad Shafiei, Hans-Peter Seidel, Weipeng Xu, Dan Casas, and Christian Theobalt. 2017b · 2017
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3D Human Pose Estimation from a Single Image via Distance Matrix Regression. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’17) . IEEE Computer Society, Washington, DC, USA, 1561–1570
Francesc Moreno-Noguer. 2017 · 2017
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Georgios Pavlakos, Luyang Zhu, Xiaowei Zhou, and Kostas Daniilidis. 2018b · 2018
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QuaterNet: A Quaternion-based Recurrent Model for Human Motion
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Learning Monocular 3D Human Pose Estimation from Multi-view Images. In Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’18) . IEEE Computer Society, Washington, DC, USA
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Neural kinematic networks for unsupervised motion retargetting. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’18) . IEEE Computer Society, Washington, DC, USA, 8639–8648
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MonoPerfCap: Human Performance Capture From Monocular Video
Weipeng Xu, Avishek Chatterjee, Michael Zollhöfer, Helge Rhodin, Dushyant Mehta, Hans-Peter Seidel, and Christian Theobalt. 2018 · 2018
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3D Human Pose Estimation in the Wild by Adversarial Learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’18) . IEEE Computer Society, Washington, DC, USA, 5255–5264
Wei Yang, Wanli Ouyang, Xiaolong Wang, Jimmy Ren, Hongsheng Li, and Xiaogang Wang. 2018 · 2018
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Skeleton Transformer Networks: 3D Human Pose and Skinned Mesh from Single RGB Image
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MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Prior
Xiaowei Zhou, Menglong Zhu, Georgios Pavlakos, Spyridon Leonardos, Konstantinos G. Derpanis, and Kostas Daniilidis. 2018 · 2018
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Exploiting temporal context for 3D human pose estimation in the wild. In Proceeding of the IEEE/CVF Conference in Computer Vision and Pattern Recognition (CVPR’19) . 3395–3404
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HoloPose: Holistic 3D Human Reconstruction In-The-Wild. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’19) . 10876–10886
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In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations
Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Gerard Pons-Moll, and Christian Theobalt. 2019 · 2019
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Learning 3D Human Dynamics from Video. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’19)
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Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network
Chen Li and Gim Hee Lee. 2019 · 2019
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3D human pose estimation in video with temporal convolutions and semi-supervised training. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR ’19) . IEEE Computer Society, Washington, DC, USA
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3D Human Pose Machines with Self-supervised Learning
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Real-time 3D Human Pose and Motion Reconstruction from Monocular RGB Videos
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Predicting 3D Human Dynamics from Video. In Proceedings of the IEEE International Conference on Computer Vision (ICCV’19)
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DeepHuman: 3D Human Reconstruction from a Single Image. In arXiv
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