REGION ENSEMBLE NETWORK: IMPROVING CONVOLUTIONAL NETWORK FOR HAND POSE ESTIMATION

Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction. Recently deep convolutional networks (ConvNet) with sophisticated design have been employed to address it, but the improvement over traditional methods is not so apparent.

Data and Resources

Cite this as

Hengkai Guo, Guijin Wang, Xinghao Chen, Cairong Zhang, Fei Qiao, Huazhong Yang (2024). Dataset: REGION ENSEMBLE NETWORK: IMPROVING CONVOLUTIONAL NETWORK FOR HAND POSE ESTIMATION. https://doi.org/10.57702/5t5gzyje

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.1109/ICIP.2017.8297136
Author Hengkai Guo
More Authors
Guijin Wang
Xinghao Chen
Cairong Zhang
Fei Qiao
Huazhong Yang
Homepage https://github.com/guohengkai/