152 citations · 1.1k across the 56 of their papers we have counts for
10 papers · 1 filter
Adaptive Affinity for Associations in Multi-Target Multi-Camera Tracking
Yunzhong Hou, Zhongdao Wang, Shengjin Wang +1
Data associations in multi-target multi-camera tracking (MTMCT) usually estimate affinity directly from re-identification (re-ID) feature distances. However, we argue that it might…
Delving into Probabilistic Uncertainty for Unsupervised Domain Adaptive Person Re-Identification
Jian Han, Ya-Li li, Shengjin Wang
Clustering-based unsupervised domain adaptive (UDA) person re-identification (ReID) reduces exhaustive annotations. However, owing to unsatisfactory feature embedding and imperfect…
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification
Zhenyu Wang, Yali Li, Ye Guo +1
Semi-supervised learning aims to leverage a large amount of unlabeled data for performance boosting. Existing works primarily focus on image classification. In this paper, we delve…
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation
Yaping Zhao, Mengqi Ji, Ruqi Huang +2
In this paper, we consider the problem of reference-based video super-resolution(RefVSR), i.e., how to utilize a high-resolution (HR) reference frame to super-resolve a low-resolut…
Towards Discriminative Representation Learning for Unsupervised Person Re-identification
Takashi Isobe, Dong Li, Lu Tian +3
In this work, we address the problem of unsupervised domain adaptation for person re-ID where annotations are available for the source domain but not for target. Previous methods t…
Do Different Tracking Tasks Require Different Appearance Models?
Zhongdao Wang, Hengshuang Zhao, Ya-Li Li +3
Tracking objects of interest in a video is one of the most popular and widely applicable problems in computer vision. However, with the years, a Cambrian explosion of use cases and…