21 citations · 71 across the 7 of their papers we have counts for
11 papers
Generalizable Re-Identification from Videos with Cycle Association
Zhongdao Wang, Zhaopeng Dou, Jingwei Zhang +4
In this paper, we are interested in learning a generalizable person re-identification (re-ID) representation from unlabeled videos. Compared with 1) the popular unsupervised re-ID…
Reliability-Aware Prediction via Uncertainty Learning for Person Image Retrieval
Zhaopeng Dou, Zhongdao Wang, Weihua Chen +2
Current person image retrieval methods have achieved great improvements in accuracy metrics. However, they rarely describe the reliability of the prediction. In this paper, we prop…
Self-Supervised Learning via Maximum Entropy Coding
Xin Liu, Zhongdao Wang, Yali Li +1
A mainstream type of current self-supervised learning methods pursues a general-purpose representation that can be well transferred to downstream tasks, typically by optimizing on…
Synthetic Data Are as Good as the Real for Association Knowledge Learning in Multi-object Tracking
Yuchi Liu, Zhongdao Wang, Xiangxin Zhou +1
Association, aiming to link bounding boxes of the same identity in a video sequence, is a central component in multi-object tracking (MOT). To train association modules, e.g., para…
CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions
Zhongdao Wang, Jingwei Zhang, Liang Zheng +4
This paper proposes a self-supervised learning method for the person re-identification (re-ID) problem, where existing unsupervised methods usually rely on pseudo labels, such as t…
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Yifan Sun, Changmao Cheng, Yuhan Zhang +4
This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity and minimize the between-class similarit…