Discrepant and Multi-Instance Proxies for Unsupervised Person Re-Identification

no code implementations • ICCV 2023 • Chang Zou, Zeqi Chen, Zhichao Cui, Yuehu Liu, Chi Zhang

To completely and accurately represent the information contained in a cluster and learn discriminative features, we propose to maintain discrepant cluster proxies and multi-instance proxies for a cluster.

Contrastive Learning Unsupervised Person Re-Identification

Artificial Intelligence Security Competition (AISC)

no code implementations • 7 Dec 2022 • Yinpeng Dong, Peng Chen, Senyou Deng, Lianji L, Yi Sun, Hanyu Zhao, Jiaxing Li, Yunteng Tan, Xinyu Liu, Yangyi Dong, Enhui Xu, Jincai Xu, Shu Xu, Xuelin Fu, Changfeng Sun, Haoliang Han, Xuchong Zhang, Shen Chen, Zhimin Sun, Junyi Cao, Taiping Yao, Shouhong Ding, Yu Wu, Jian Lin, Tianpeng Wu, Ye Wang, Yu Fu, Lin Feng, Kangkang Gao, Zeyu Liu, Yuanzhe Pang, Chengqi Duan, Huipeng Zhou, Yajie Wang, Yuhang Zhao, Shangbo Wu, Haoran Lyu, Zhiyu Lin, YiFei Gao, Shuang Li, Haonan Wang, Jitao Sang, Chen Ma, Junhao Zheng, Yijia Li, Chao Shen, Chenhao Lin, Zhichao Cui, Guoshuai Liu, Huafeng Shi, Kun Hu, Mengxin Zhang

The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems.

Autonomous Driving Face Recognition +1

Dual Clustering Co-teaching with Consistent Sample Mining for Unsupervised Person Re-Identification

no code implementations • 7 Oct 2022 • Zeqi Chen, Zhichao Cui, Chi Zhang, Jiahuan Zhou, Yuehu Liu

However, training two networks with a set of noisy pseudo labels reduces the complementarity of the two networks and results in label noise accumulation.

Clustering Pseudo Label +1