This is the caffe implementation for Context-Aware Deep Spatio-Temporal Network for Hand Pose Estimation from Depth Images.

Introduction

We leverage an LSTM for capturing spatio-temporal context in the depth image sequences.

Datasets

Method	NYU	ICVL
HeatMap	21.02	-
LRF	-	12.56
DeepPrior	19.73	9.42
Feedback	15.97	-
DeepModel	16.90	11.55
Lie-X	14.51	-
CrossingNet	-	10.22
LSN	-	8.20
CADSN	14.83	8.04

Result

Qualitative

Citation

If you find the code is helpful for you, please kindly cite this paper in your publications:

@article{wu2018context,
  title={Context-Aware Deep Spatiotemporal Network for Hand Pose Estimation From Depth Images},
  author={Wu, Yiming and Ji, Wei and Li, Xi and Wang, Gang and Yin, Jianwei and Wu, Fei},
  journal={IEEE transactions on cybernetics},
  volume={50},
  number={2},
  pages={787--797},
  year={2018},
  publisher={IEEE}
}