Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction

no code implementations • ECCV 2020 • Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek, Shreyas Hampali, Mahdi Rad, Zhaohui Zhang, Shipeng Xie, Mingxiu Chen, Boshen Zhang, Fu Xiong, Yang Xiao, Zhiguo Cao, Junsong Yuan, Pengfei Ren, Weiting Huang, Haifeng Sun, Marek Hrúz, Jakub Kanis, Zdeněk Krňoul, Qingfu Wan, Shile Li, Linlin Yang, Dongheui Lee, Angela Yao, Weiguo Zhou, Sijia Mei, Yun-hui Liu, Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Philippe Weinzaepfel, Romain Brégier, Grégory Rogez, Vincent Lepetit, Tae-Kyun Kim

To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.

3D Hand Pose Estimation

HMTNet:3D Hand Pose Estimation from Single Depth Image Based on Hand Morphological Topology

no code implementations • 12 Nov 2019 • Weiguo Zhou, Xin Jiang, Chen Chen, Sijia Mei, Yun-hui Liu

In this paper, we propose a method that takes advantage of human hand morphological topology (HMT) structure to improve the pose estimation performance.

Robotics Human-Computer Interaction

Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images

no code implementations • 24 Feb 2019 • Shengfan Wang, Xin Jiang, Jie Zhao, Xiaoman Wang, Weiguo Zhou, Yun-hui Liu, Fellow IEEE

This paper presents an efficient neural network model to generate robotic grasps with high resolution images.

Robotics