46 citations · 63 across the 3 of their papers we have counts for
5 papers · 1 filter
An Improved Normed-Deformable Convolution for Crowd Counting
Xin Zhong, Zhaoyi Yan, Jing Qin +2
In recent years, crowd counting has become an important issue in computer vision. In most methods, the density maps are generated by convolving with a Gaussian kernel from the grou…
Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting
Binghui Chen, Zhaoyi Yan, Ke Li +4
In crowd counting, due to the problem of laborious labelling, it is perceived intractability of collecting a new large-scale dataset which has plentiful images with large diversity…
Crowd Counting via Perspective-Guided Fractional-Dilation Convolution
Zhaoyi Yan, Ruimao Zhang, Hongzhi Zhang +2
Crowd counting is critical for numerous video surveillance scenarios. One of the main issues in this task is how to handle the dramatic scale variations of pedestrians caused by th…
Perspective-Guided Convolution Networks for Crowd Counting
Zhaoyi Yan, Yuchen Yuan, Wangmeng Zuo +4
In this paper, we propose a novel perspective-guided convolution (PGC) for convolutional neural network (CNN) based crowd counting (i.e. PGCNet), which aims to overcome the dramati…
Shift-Net: Image Inpainting via Deep Feature Rearrangement
Zhaoyi Yan, Xiaoming Li, Mu Li +2
Deep convolutional networks (CNNs) have exhibited their potential in image inpainting for producing plausible results. However, in most existing methods, e.g., context encoder, the…