no code implementations • CVPR 2023 • YuAn Wang, Kun Yu, Chen Chen, Xiyuan Hu, Silong Peng
To address this issue, we propose a Spatial-Frequency Dynamic Graph method to exploit the relation-aware features in spatial and frequency domains via dynamic graph learning.
1 code implementation • 21 Apr 2021 • Shaoyu Zhang, Chen Chen, Xiyuan Hu, Silong Peng
Existing methods usually modify the classification loss to increase the learning focus on tail classes, which unexpectedly sacrifice the performance on head classes.
1 code implementation • 7 Sep 2020 • Min Cao, Chen Chen, Hao Dou, Xiyuan Hu, Silong Peng, Arjan Kuijper
Most existing person re-identification methods compute pairwise similarity by extracting robust visual features and learning the discriminative metric.
no code implementations • 1 May 2020 • Hao Dou, Chen Chen, Xiyuan Hu, Zuxing Xuan, Zhisen Hu, Silong Peng
Generative Adversarial Networks (GAN) have been employed for face super resolution but they bring distorted facial details easily and still have weakness on recovering realistic texture.
no code implementations • ECCV 2018 • Zhenfeng Fan, Xiyuan Hu, Chen Chen, Silong Peng
The dense correspondence goal is revisited in two perspectives: semantic and topological correspondence.
no code implementations • 25 May 2018 • Chen Chen, Min Cao, Xiyuan Hu, Silong Peng
Ideally person re-identification seeks for perfect feature representation and metric model that re-identify all various pedestrians well in non-overlapping views at different locations with different camera configurations, which is very challenging.