63 citations · 108 across the 9 of their papers we have counts for
9 papers
Prototype Matters: Modality-unified Prototype Self-distillation for Unsupervised Visible-infrared Person Re-identification
Menglin Wang, Xiaojin Gong
Estimating reliable cross-modality association is crucial to unsupervised visible-infrared person re-ID. While optimal transport is shown to be a practical solution for cross-modal…
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…
Learning Intra and Inter-Camera Invariance for Isolated Camera Supervised Person Re-identification
Menglin Wang, Xiaojin Gong
Supervised person re-identification assumes that a person has images captured under multiple cameras. However when cameras are placed in distance, a person rarely appears in more t…
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…
Offline-Online Associated Camera-Aware Proxies for Unsupervised Person Re-identification
Menglin Wang, Jiachen Li, Baisheng Lai +2
Recently, unsupervised person re-identification (Re-ID) has received increasing research attention due to its potential for label-free applications. A promising way to address unsu…
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…