8 citations · 16 across the 5 of their papers we have counts for
6 papers · 1 filter
Modality-Aware Bias Mitigation and Invariance Learning for Unsupervised Visible-Infrared Person Re-Identification
Menglin Wang, Xiaojin Gong, Jiachen Li +1
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match individuals across visible and infrared cameras without relying on any annotation. Given the signif…
Prior-Constrained Association Learning for Fine-Grained Generalized Category Discovery
Menglin Wang, Zhun Zhong, Xiaojin Gong
This paper addresses generalized category discovery (GCD), the task of clustering unlabeled data from potentially known or unknown categories with the help of labeled instances fro…
Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
Jiachen Li, Menglin Wang, Xiaojin Gong
Multi-grained features extracted from convolutional neural networks (CNNs) have demonstrated their strong discrimination ability in supervised person re-identification (Re-ID) task…
Camera-aware Proxies for Unsupervised Person Re-Identification
Menglin Wang, Baisheng Lai, Jianqiang Huang +2
This paper tackles the purely unsupervised person re-identification (Re-ID) problem that requires no annotations. Some previous methods adopt clustering techniques to generate pseu…
Deep Active Learning for Video-based Person Re-identification
Menglin Wang, Baisheng Lai, Zhongming Jin +3
It is prohibitively expensive to annotate a large-scale video-based person re-identification (re-ID) dataset, which makes fully supervised methods inapplicable to real-world deploy…
Dynamic Spatio-temporal Graph-based CNNs for Traffic Prediction
Ken Chen, Fei Chen, Baisheng Lai +8
Forecasting future traffic flows from previous ones is a challenging problem because of their complex and dynamic nature of spatio-temporal structures. Most existing graph-based CN…