103 citations · 126 across the 17 of their papers we have counts for
7 papers · 1 filter
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
Jierun Chen, Shiu-hong Kao, Hao He +4
To design fast neural networks, many works have been focusing on reducing the number of floating-point operations (FLOPs). We observe that such reduction in FLOPs, however, does no…
TVConv: Efficient Translation Variant Convolution for Layout-aware Visual Processing
Jierun Chen, Tianlang He, Weipeng Zhuo +3
As convolution has empowered many smart applications, dynamic convolution further equips it with the ability to adapt to diverse inputs. However, the static and dynamic convolution…
Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification
Haoyue Bai, Song Wen, S. -H. Gary Chan
Labeled crowd scene images are expensive and scarce. To significantly reduce the requirement of the labeled images, we propose ColorCount, a novel CNN-based approach by combining s…
Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting
Haoyue Bai, S. -H. Gary Chan
We study video crowd counting, which is to estimate the number of objects (people in this paper) in all the frames of a video sequence. Previous work on crowd counting is mostly on…
Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty
Jierun Chen, Song Wen, S. -H. Gary Chan
Image demosaicking and denoising are the two key fundamental steps in digital camera pipelines, aiming to reconstruct clean color images from noisy luminance readings. In this pape…
A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory Signal
Haoyue Bai, Jiageng Mao, S. -H. Gary Chan
Single image crowd counting is a challenging computer vision problem with wide applications in public safety, city planning, traffic management, etc. With the recent development of…
Crowd Counting on Images with Scale Variation and Isolated Clusters
Haoyue Bai, Song Wen, S. -H. Gary Chan
Crowd counting is to estimate the number of objects (e.g., people or vehicles) in an image of unconstrained congested scenes. Designing a general crowd counting algorithm applicabl…