12 citations · 35 across the 6 of their papers we have counts for
7 papers
PressureVision: Estimating Hand Pressure from a Single RGB Image
Patrick Grady, Chengcheng Tang, Samarth Brahmbhatt +4
People often interact with their surroundings by applying pressure with their hands. While hand pressure can be measured by placing pressure sensors between the hand and the enviro…
Dual Grid Net: hand mesh vertex regression from single depth maps
Chengde Wan, Thomas Probst, Luc Van Gool +1
We present a method for recovering the dense 3D surface of the hand by regressing the vertex coordinates of a mesh model from a single depth map. To this end, we use a two-stage 2D…
Dense 3D Regression for Hand Pose Estimation
Chengde Wan, Thomas Probst, Luc Van Gool +1
We present a simple and effective method for 3D hand pose estimation from a single depth frame. As opposed to previous state-of-the-art methods based on holistic 3D regression, our…
Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation
Chengde Wan, Thomas Probst, Luc Van Gool +1
State-of-the-art methods for 3D hand pose estimation from depth images require large amounts of annotated training data. We propose to model the statistical relationships of 3D han…
Deep Learning on Lie Groups for Skeleton-based Action Recognition
Zhiwu Huang, Chengde Wan, Thomas Probst +1
In recent years, skeleton-based action recognition has become a popular 3D classification problem. State-of-the-art methods typically first represent each motion sequence as a high…
Direction matters: hand pose estimation from local surface normals
Chengde Wan, Angela Yao, Luc Van Gool
We present a hierarchical regression framework for estimating hand joint positions from single depth images based on local surface normals. The hierarchical regression follows the…