32 citations · 71 across the 7 of their papers we have counts for
3 papers · 1 filter
LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localization
Zhiwei Chen, Changan Wang, Yabiao Wang +6
Weakly supervised object localization (WSOL) aims to learn object localizer solely by using image-level labels. The convolution neural network (CNN) based techniques often result i…
Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework
Qingyu Song, Changan Wang, Zhengkai Jiang +6
Localizing individuals in crowds is more in accordance with the practical demands of subsequent high-level crowd analysis tasks than simply counting. However, existing localization…
Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting
Changan Wang, Qingyu Song, Boshen Zhang +7
Recently, the problem of inaccurate learning targets in crowd counting draws increasing attention. Inspired by a few pioneering work, we solve this problem by trying to predict the…