most citedUncertainty Modeling for Out-of-Distribution Generalization

71 citations · 100 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV202211 cited

Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate Domains

Yongxing Dai, Yifan Sun, Jun Liu +3

Cross-domain person re-identification (re-ID), such as unsupervised domain adaptive (UDA) re-ID, aims to transfer the identity-discriminative knowledge from the source to the targe…

cs.CV202271 cited

Uncertainty Modeling for Out-of-Distribution Generalization

Xiaotong Li, Yongxing Dai, Yixiao Ge +3

Though remarkable progress has been achieved in various vision tasks, deep neural networks still suffer obvious performance degradation when tested in out-of-distribution scenarios…

cs.CV20217 cited

IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID

Yongxing Dai, Jun Liu, Yifan Sun +3

Unsupervised domain adaptive person re-identification (UDA re-ID) aims at transferring the labeled source domain's knowledge to improve the model's discriminability on the unlabele…

cs.CV202111 cited

Generalizable Person Re-identification with Relevance-aware Mixture of Experts

Yongxing Dai, Xiaotong Li, Jun Liu +2

Domain generalizable (DG) person re-identification (ReID) is a challenging problem because we cannot access any unseen target domain data during training. Almost all the existing D…

cs.CV2021

Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification

Yongxing Dai, Jun Liu, Yan Bai +2

Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some rece…