131 citations · 196 across the 6 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.CV2019★ 34 cited
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…
cs.CV2019
Recognizing Part Attributes with Insufficient Data
Xiangyun Zhao, Yi Yang, Feng Zhou +4
Recognizing attributes of objects and their parts is important to many computer vision applications. Although great progress has been made to apply object-level recognition, recogn…
cs.CV2019★ 10 cited
Deep Density-aware Count Regressor
Zhuojun Chen, Junhao Cheng, Yuchen Yuan +3
We seek to improve crowd counting as we perceive limits of currently prevalent density map estimation approach on both prediction accuracy and time efficiency. We leverage multilev…