VIBE: Video Inference for Human Body Pose and Shape Estimation
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[1] Xiaowei Zhou,et al. Learning to Estimate 3D Human Pose and Shape from a Single Color Image , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] Rishabh Dabral,et al. Structure-Aware and Temporally Coherent 3D Human Pose Estimation , 2017, ArXiv.
[3] Dimitrios Tzionas,et al. Expressive Body Capture: 3D Hands, Face, and Body From a Single Image , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Cristian Sminchisescu,et al. Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] David J. Fleet,et al. 3D People Tracking with Gaussian Process Dynamical Models , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[6] Michael J. Black,et al. The Naked Truth: Estimating Body Shape Under Clothing , 2008, ECCV.
[7] Michael J. Black,et al. Learning and Tracking Cyclic Human Motion , 2000, NIPS.
[8] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[9] Otmar Hilliges,et al. Structured Prediction Helps 3D Human Motion Modelling , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[10] Ankur Agarwal,et al. Recovering 3D human pose from monocular images , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] G. Johansson. Visual perception of biological motion and a model for its analysis , 1973 .
[12] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[13] Andrew Zisserman,et al. Exploiting Temporal Context for 3D Human Pose Estimation in the Wild , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Peter V. Gehler,et al. DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Michael J. Black,et al. MoSh: motion and shape capture from sparse markers , 2014, ACM Trans. Graph..
[16] Dario Pavllo,et al. 3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Shrikanth Narayanan,et al. NTUA-SLP at SemEval-2018 Task 1: Predicting Affective Content in Tweets with Deep Attentive RNNs and Transfer Learning , 2018, *SEMEVAL.
[18] Mi Bouaricha,et al. Nonlinear Equations , 2000 .
[19] Hans-Peter Seidel,et al. VNect , 2017, ACM Trans. Graph..
[20] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[21] Trevor Darrell,et al. Inferring 3D structure with a statistical image-based shape model , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[22] Pascal Fua,et al. Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision , 2016, 2017 International Conference on 3D Vision (3DV).
[23] Tie-Yan Liu,et al. Adversarial Neural Machine Translation , 2017, ACML.
[24] Cordelia Schmid,et al. BodyNet: Volumetric Inference of 3D Human Body Shapes , 2018, ECCV.
[25] Yaser Sheikh,et al. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Abhishek Sharma,et al. Learning 3D Human Pose from Structure and Motion , 2017, ECCV.
[27] Bernhard Schölkopf,et al. From Variational to Deterministic Autoencoders , 2019, ICLR.
[28] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[29] Lorenzo Torresani,et al. Detect-and-Track: Efficient Pose Estimation in Videos , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[30] Andrew Zisserman,et al. Sim2real transfer learning for 3D human pose estimation: motion to the rescue , 2019, NeurIPS.
[31] Liu Wu,et al. Human Mesh Recovery From Monocular Images via a Skeleton-Disentangled Representation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[32] Jan Kautz,et al. Unsupervised Image-to-Image Translation Networks , 2017, NIPS.
[33] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[34] Yinghao Huang,et al. Towards Accurate Marker-Less Human Shape and Pose Estimation over Time , 2017, 2017 International Conference on 3D Vision (3DV).
[35] José M. F. Moura,et al. Adversarial Geometry-Aware Human Motion Prediction , 2018, ECCV.
[36] David C. Hogg. Model-based vision: a program to see a walking person , 1983, Image Vis. Comput..
[37] Michael J. Black,et al. Combined discriminative and generative articulated pose and non-rigid shape estimation , 2007, NIPS.
[38] Sebastian Thrun,et al. SCAPE: shape completion and animation of people , 2005, SIGGRAPH '05.
[39] Wei Chen,et al. Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets , 2017, NAACL.
[40] Pascal Fua,et al. XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera , 2019, ACM Trans. Graph..
[41] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Ben Taskar,et al. MODEC: Multimodal Decomposable Models for Human Pose Estimation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[43] Fabio Viola,et al. The Kinetics Human Action Video Dataset , 2017, ArXiv.
[44] Peter V. Gehler,et al. Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation , 2018, 2018 International Conference on 3D Vision (3DV).
[45] Ignas Budvytis,et al. Indirect deep structured learning for 3D human body shape and pose prediction , 2017, BMVC.
[46] Nikolaus F. Troje,et al. AMASS: Archive of Motion Capture As Surface Shapes , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[47] Yi Zhou,et al. On the Continuity of Rotation Representations in Neural Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Andrew Zisserman,et al. Sim2real transfer learning for 3D pose estimation: motion to the rescue , 2019, ArXiv.
[49] Hao Li,et al. PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[50] Jitendra Malik,et al. End-to-End Recovery of Human Shape and Pose , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[51] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[52] Andrew Zisserman,et al. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[53] Weiyu Zhang,et al. From Actemes to Action: A Strongly-Supervised Representation for Detailed Action Understanding , 2013, 2013 IEEE International Conference on Computer Vision.
[54] Christian Theobalt,et al. Single-Shot Multi-person 3D Pose Estimation from Monocular RGB , 2017, 2018 International Conference on 3D Vision (3DV).
[55] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[56] Bernhard Schölkopf,et al. Wasserstein Auto-Encoders , 2017, ICLR.
[57] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[58] Iasonas Kokkinos,et al. HoloPose: Holistic 3D Human Reconstruction In-The-Wild , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[59] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[60] Kostas Daniilidis,et al. Convolutional Mesh Regression for Single-Image Human Shape Reconstruction , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[61] Ersin Yumer,et al. Self-supervised Learning of Motion Capture , 2017, NIPS.
[62] Emre Akbas,et al. Self-Supervised Learning of 3D Human Pose Using Multi-View Geometry , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[63] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[64] Peter V. Gehler,et al. Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image , 2016, ECCV.
[65] Bodo Rosenhahn,et al. Supplementary Material to: Recovering Accurate 3D Human Pose in The Wild Using IMUs and a Moving Camera , 2018 .
[66] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[67] Peter V. Gehler,et al. Unite the People: Closing the Loop Between 3D and 2D Human Representations , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[68] Jitendra Malik,et al. Learning 3D Human Dynamics From Video , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[69] Zicheng Liu,et al. HP-GAN: Probabilistic 3D Human Motion Prediction via GAN , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[70] Bernt Schiele,et al. PoseTrack: A Benchmark for Human Pose Estimation and Tracking , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[71] James J. Little,et al. Exploiting Temporal Information for 3D Human Pose Estimation , 2017, ECCV.
[72] Emre Akbas,et al. MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network , 2018, ECCV.
[73] Yaser Sheikh,et al. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[74] Michael J. Black,et al. Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).