36 citations · 73 across the 11 of their papers we have counts for
4 papers · 1 filter
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger +21
In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled?…
V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map
Gyeongsik Moon, Ju Yong Chang, Kyoung Mu Lee
Most of the existing deep learning-based methods for 3D hand and human pose estimation from a single depth map are based on a common framework that takes a 2D depth map and directl…
Holistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation
Gyeongsik Moon, Ju Yong Chang, Yumin Suh +1
We propose a novel approach to 3D human pose estimation from a single depth map. Recently, convolutional neural network (CNN) has become a powerful paradigm in computer vision. Man…
2D-3D Pose Consistency-based Conditional Random Fields for 3D Human Pose Estimation
Ju Yong Chang, Kyoung Mu Lee
This study considers the 3D human pose estimation problem in a single RGB image by proposing a conditional random field (CRF) model over 2D poses, in which the 3D pose is obtained…