1 code implementation • 26 Apr 2024 • Pengwei Xie, Rui Chen, Siang Chen, Yuzhe Qin, Fanbo Xiang, Tianyu Sun, Jing Xu, Guijin Wang, Hao Su
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots.
no code implementations • 23 Apr 2024 • Junli Ren, YiKai Liu, Yingru Dai, Guijin Wang
Within the path planner, we present and integrate a terrain estimator that enables the robot to select waypoints on terrains with higher traversability while effectively avoiding obstacles.
1 code implementation • IEEE ROBOTICS AND AUTOMATION LETTERS 2023 • Siang Chen, Wei Tang, Pengwei Xie, Wenming Yang, Guijin Wang
Specifically, Gaussian encoding and the grid-based strategy are applied to predict grasp heatmaps as guidance to aggregate local points into graspable regions and provide global semantic information.
Ranked #4 on Robotic Grasping on GraspNet-1Billion
1 code implementation • IEEE Transactions on Image Processing 2024 • Woomin Myung, Nan Su, Jing-Hao Xue, Guijin Wang
Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition.
Ranked #1 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • 12 Mar 2024 • Bowen Liu, Wei Liu, Siang Chen, Pengwei Xie, Guijin Wang
The goal of object pose estimation is to visually determine the pose of a specific object in the RGB-D input.
no code implementations • 28 Jan 2023 • Yuzhen Qin, Li Sun, Hui Chen, Wei-Qiang Zhang, Wenming Yang, Jintao Fei, Guijin Wang
However, it is challenging to develop a single-lead-based ECG interpretation model for multiple diseases diagnosis due to the lack of some key disease information.
no code implementations • 23 Nov 2022 • Yang Li, Guijin Wang, Zhourui Xia, Wenming Yang, Li Sun
Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs).
no code implementations • 7 Jun 2020 • Xiaoyu Feng, Zhuqing Yuan, Guijin Wang, Yongpan Liu
For example, the model is first pruned on the cloud and then transferred from cloud to end by UDA.
no code implementations • 26 Feb 2019 • Guijin Wang, Cairong Zhang, Xinghao Chen, Xiangyang Ji, Jing-Hao Xue, Hang Wang
To mitigate these limitations and promote further research on hand pose estimation from stereo images, we propose a new large-scale binocular hand pose dataset called THU-Bi-Hand, offering a new perspective for fingertip localization.
no code implementations • IEEE Access 2018 • Xinghao Chen, Guijin Wang, Cairong Zhang, Tae-Kyun Kim, Xiangyang Ji
The semantic segmentation network assigns semantic labels for each point in the point set.
Ranked #7 on Hand Pose Estimation on MSRA Hands
no code implementations • 26 Apr 2018 • Yi Wei, Guijin Wang, Cairong Zhang, Hengkai Guo, Xinghao Chen, Huazhong Yang
Different from previous works, we propose a new framework, named Two-Stream Binocular Network (TSBnet) to detect fingertips from binocular images directly.
no code implementations • 2 Apr 2018 • Cairong Zhang, Guijin Wang, Hengkai Guo, Xinghao Chen, Fei Qiao, Huazhong Yang
In the reality of HMI, joints in fingers stretching out, especially corresponding fingertips, are much more important than other joints.
1 code implementation • CVPR 2018 • Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger, Gyeongsik Moon, Ju Yong Chang, Kyoung Mu Lee, Pavlo Molchanov, Jan Kautz, Sina Honari, Liuhao Ge, Junsong Yuan, Xinghao Chen, Guijin Wang, Fan Yang, Kai Akiyama, Yang Wu, Qingfu Wan, Meysam Madadi, Sergio Escalera, Shile Li, Dongheui Lee, Iason Oikonomidis, Antonis Argyros, Tae-Kyun Kim
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
Ranked #5 on Hand Pose Estimation on HANDS 2017
1 code implementation • 11 Aug 2017 • Xinghao Chen, Guijin Wang, Hengkai Guo, Cairong Zhang
The proposed method extracts regions from the feature maps of convolutional neural network under the guide of an initially estimated pose, generating more optimal and representative features for hand pose estimation.
Ranked #8 on Hand Pose Estimation on HANDS 2017
no code implementations • 10 Aug 2017 • Xinghao Chen, Hengkai Guo, Guijin Wang, Li Zhang
Dynamic hand gesture recognition has attracted increasing interests because of its importance for human computer interaction.
Ranked #6 on Hand Gesture Recognition on DHG-28
no code implementations • 23 Jul 2017 • Hengkai Guo, Guijin Wang, Xinghao Chen, Cairong Zhang
3D hand pose estimation from single depth image is an important and challenging problem for human-computer interaction.
Ranked #4 on Pose Estimation on ITOP top-view
no code implementations • 8 Feb 2017 • Hengkai Guo, Guijin Wang, Xinghao Chen, Cairong Zhang, Fei Qiao, Huazhong Yang
Hand pose estimation from monocular depth images is an important and challenging problem for human-computer interaction.
Ranked #11 on Hand Pose Estimation on MSRA Hands
no code implementations • 23 Dec 2016 • Hengkai Guo, Guijin Wang, Xinghao Chen
Accurate detection of fingertips in depth image is critical for human-computer interaction.