5 citations · 8 across the 3 of their papers we have counts for
5 papers
DecAug: Augmenting HOI Detection via Decomposition
Yichen Xie, Hao-Shu Fang, Dian Shao +2
Human-object interaction (HOI) detection requires a large amount of annotated data. Current algorithms suffer from insufficient training samples and category imbalance within datas…
Transferable Active Grasping and Real Embodied Dataset
Xiangyu Chen, Zelin Ye, Jiankai Sun +4
Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects. We adopt a reinforcement learning (RL)…
GraspNet: A Large-Scale Clustered and Densely Annotated Dataset for Object Grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou +1
Object grasping is critical for many applications, which is also a challenging computer vision problem. However, for the clustered scene, current researches suffer from the problem…
Cross-Domain Adaptation for Animal Pose Estimation
Jinkun Cao, Hongyang Tang, Hao-Shu Fang +3
In this paper, we are interested in pose estimation of animals. Animals usually exhibit a wide range of variations on poses and there is no available animal pose dataset for traini…
Estimating 6D Pose From Localizing Designated Surface Keypoints
Zelin Zhao, Gao Peng, Haoyu Wang +3
In this paper, we present an accurate yet effective solution for 6D pose estimation from an RGB image. The core of our approach is that we first designate a set of surface points o…