Spatial-aware stacked regression network for real-time 3D hand pose estimation

[1]  Kyoung Mu Lee,et al.  V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[2]  Luc Van Gool,et al.  Dense 3D Regression for Hand Pose Estimation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[3]  Tae-Kyun Kim,et al.  Latent Regression Forest: Structured Estimation of 3D Hand Poses , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Yichen Wei,et al.  Simple Baselines for Human Pose Estimation and Tracking , 2018, ECCV.

[5]  Jian Sun,et al.  Cascaded hand pose regression , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Luc Van Gool,et al.  Self-Supervised 3D Hand Pose Estimation Through Training by Fitting , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Antti Oulasvirta,et al.  Real-Time Joint Tracking of a Hand Manipulating an Object from RGB-D Input , 2016, ECCV.

[8]  Fei Qiao,et al.  Region ensemble network: Improving convolutional network for hand pose estimation , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[9]  Tae-Kyun Kim,et al.  SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds , 2018, IEEE Access.

[10]  Tae-Kyun Kim,et al.  Latent Regression Forest: Structured Estimation of 3D Articulated Hand Posture , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Antti Oulasvirta,et al.  Fast and robust hand tracking using detection-guided optimization , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Yichen Wei,et al.  Model-Based Deep Hand Pose Estimation , 2016, IJCAI.

[13]  Daniel Thalmann,et al.  Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  Luc Van Gool,et al.  Crossing Nets: Dual Generative Models with a Shared Latent Space for Hand Pose Estimation , 2017, ArXiv.

[15]  Yu Liu,et al.  Correlation Congruence for Knowledge Distillation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[16]  Sergio Escalera,et al.  Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[17]  Jianrong Tan,et al.  A survey on 3D hand pose estimation: Cameras, methods, and datasets , 2019, Pattern Recognit..

[18]  Andrew W. Fitzgibbon,et al.  Learning an efficient model of hand shape variation from depth images , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Chen Qian,et al.  Realtime and Robust Hand Tracking from Depth , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Dongheui Lee,et al.  Point-To-Pose Voting Based Hand Pose Estimation Using Residual Permutation Equivariant Layer , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Jia Deng,et al.  Stacked Hourglass Networks for Human Pose Estimation , 2016, ECCV.

[22]  Jianfei Cai,et al.  3D Hand Shape and Pose Estimation from a Single RGB Image (Supplementary Material) , 2019 .

[23]  Cordelia Schmid,et al.  Learning Joint Reconstruction of Hands and Manipulated Objects , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Qi Qi,et al.  AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation , 2020, AAAI.

[25]  Dacheng Tao,et al.  Learning Student Networks via Feature Embedding , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[26]  Yi Sun,et al.  CrossInfoNet: Multi-Task Information Sharing Based Hand Pose Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[27]  Greg Mori,et al.  Similarity-Preserving Knowledge Distillation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[28]  Jin Young Choi,et al.  Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons , 2018, AAAI.

[29]  Anastasios Tefas,et al.  Learning Deep Representations with Probabilistic Knowledge Transfer , 2018, ECCV.

[30]  Horst Bischof,et al.  MURAUER: Mapping Unlabeled Real Data for Label AUstERity , 2019, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

[31]  Luc Van Gool,et al.  Motion Capture of Hands in Action Using Discriminative Salient Points , 2012, ECCV.

[32]  Kaisheng Ma,et al.  Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[33]  Yang Xiao,et al.  A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation From a Single Depth Image , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[34]  Yan Lu,et al.  Relational Knowledge Distillation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[35]  Trevor Darrell,et al.  Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[36]  Vincent Lepetit,et al.  Generalized Feedback Loop for Joint Hand-Object Pose Estimation , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Yoshua Bengio,et al.  FitNets: Hints for Thin Deep Nets , 2014, ICLR.

[38]  Andrew W. Fitzgibbon,et al.  Accurate, Robust, and Flexible Real-time Hand Tracking , 2015, CHI.

[39]  Dejun Zhang,et al.  SO-HandNet: Self-Organizing Network for 3D Hand Pose Estimation With Semi-Supervised Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[40]  Chen Change Loy,et al.  Learning Lightweight Lane Detection CNNs by Self Attention Distillation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[41]  Andrea Tagliasacchi,et al.  Robust Articulated-ICP for Real-Time Hand Tracking , 2015 .

[42]  Daniel Thalmann,et al.  Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[43]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[44]  Tae-Kyun Kim,et al.  Pushing the Envelope for RGB-Based Dense 3D Hand Pose Estimation via Neural Rendering , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  Ruigang Yang,et al.  Real-Time Simultaneous Pose and Shape Estimation for Articulated Objects Using a Single Depth Camera , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[46]  C. Theobalt,et al.  Generative Model-Based Loss to the Rescue: A Method to Overcome Annotation Errors for Depth-Based Hand Pose Estimation , 2020, 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020).

[47]  Yong-Liang Yang,et al.  HandMap: Robust Hand Pose Estimation via Intermediate Dense Guidance Map Supervision , 2018, ECCV.

[48]  Nikos Komodakis,et al.  Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer , 2016, ICLR.

[49]  Vincent Lepetit,et al.  Feature Mapping for Learning Fast and Accurate 3D Pose Inference from Synthetic Images , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.