553 citations
- Beihang UniversityCN66 papers
- Microsoft Research Asia (China)CN12 papers
- Chinese Academy of SciencesCN9 papers
- Tsinghua UniversityCN6 papers
- National Cheng Kung UniversityTW4 papers
- University of Chinese Academy of SciencesCN4 papers
- Institute of SoftwareCN3 papers
- Zhejiang UniversityCN3 papers
- CAS Key Laboratory of Quantum Information, USTCCN2 papers
- Nankai UniversityCN2 papers
- State Key Laboratory of Computer Science2 papers
- State Key Laboratory of Low-Dimensional Quantum Physics2 papers
67 papers
Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook
Huang Zhang, Changshuo Wang, Shengwei Tian +4
In recent years, point cloud representation has become one of the research hotspots in the field of computer vision, and has been widely used in many fields, such as autonomous dri…
FuseFPS: Accelerating Farthest Point Sampling with Fusing KD-tree Construction for Point Clouds
Meng Han, Liang Wang, Limin Xiao +5
Point cloud analytics has become a critical workload for embedded and mobile platforms across various applications. Farthest point sampling (FPS) is a fundamental and widely used k…
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
Yang Zhou, Yongjian Wu, Zihua Wang +5
Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manua…
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction
Jiahao Ji, Jingyuan Wang, Zhe Jiang +2
High-performance traffic flow prediction model designing, a core technology of Intelligent Transportation System, is a long-standing but still challenging task for industrial and a…
Accelerating Sparse Approximate Matrix Multiplication on GPUs
Xiaoyan Liu, Yi Liu, Ming Dun +4
Although the matrix multiplication plays a vital role in computational linear algebra, there are few efficient solutions for matrix multiplication of the near-sparse matrices. The…
Bi-GCN: Binary Graph Convolutional Network
Junfu Wang, Yunhong Wang, Zhen Yang +2
Graph Neural Networks (GNNs) have achieved tremendous success in graph representation learning. Unfortunately, current GNNs usually rely on loading the entire attributed graph into…