4 citations · 9 across the 5 of their papers we have counts for
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cs.CV2023
Combining Past, Present and Future: A Self-Supervised Approach for Class Incremental Learning
Xiaoshuang Chen, Zhongyi Sun, Ke Yan +2
Class Incremental Learning (CIL) aims to handle the scenario where data of novel classes occur continuously and sequentially. The model should recognize the sequential novel classe…
cs.CV2022★ 4 cited
Reinforcing Local Feature Representation for Weakly-Supervised Dense Crowd Counting
Xiaoshuang Chen, Hongtao Lu
Fully-supervised crowd counting is a laborious task due to the large amounts of annotations. Few works focus on weekly-supervised crowd counting, where only the global crowd number…
cs.CV2021★ 1 cited
PANet: Perspective-Aware Network with Dynamic Receptive Fields and Self-Distilling Supervision for Crowd Counting
Xiaoshuang Chen, Yiru Zhao, Yu Qin +4
Crowd counting aims to learn the crowd density distributions and estimate the number of objects (e.g. persons) in images. The perspective effect, which significantly influences the…