6 citations · 14 across the 5 of their papers we have counts for
9 papers · 1 filter
X-NeRF: Explicit Neural Radiance Field for Multi-Scene 360 Insufficient RGB-D Views
Haoyi Zhu, Hao-Shu Fang, Cewu Lu
Neural Radiance Fields (NeRFs), despite their outstanding performance on novel view synthesis, often need dense input views. Many papers train one model for each scene respectively…
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…
DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection
Hao-Shu Fang, Yichen Xie, Dian Shao +1
Recent years, human-object interaction (HOI) detection has achieved impressive advances. However, conventional two-stage methods are usually slow in inference. On the other hand, e…
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…
Attribute Restoration Framework for Anomaly Detection
Chaoqin Huang, Fei Ye, Jinkun Cao +3
With the recent advances in deep neural networks, anomaly detection in multimedia has received much attention in the computer vision community. While reconstruction-based methods h…
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…