2 citations · 3 across the 3 of their papers we have counts for
4 papers
NeuMatC: A General Neural Framework for Fast Parametric Matrix Operation
Chuan Wang, Xi-le Zhao, Zhilong Han +3
Matrix operations (e.g., inversion and singular value decomposition (SVD)) are fundamental in science and engineering. In many emerging real-world applications (such as wireless co…
Polyline Path Masked Attention for Vision Transformer
Zhongchen Zhao, Chaodong Xiao, Hui Lin +3
Global dependency modeling and spatial position modeling are two core issues of the foundational architecture design in current deep learning frameworks. Recently, Vision Transform…
Semi-supervised Counting via Pixel-by-pixel Density Distribution Modelling
Hui Lin, Zhiheng Ma, Rongrong Ji +4
This paper focuses on semi-supervised crowd counting, where only a small portion of the training data are labeled. We formulate the pixel-wise density value to regress as a probabi…
Gramformer: Learning Crowd Counting via Graph-Modulated Transformer
Hui Lin, Zhiheng Ma, Xiaopeng Hong +2
Transformer has been popular in recent crowd counting work since it breaks the limited receptive field of traditional CNNs. However, since crowd images always contain a large numbe…