5 citations · 9 across the 5 of their papers we have counts for
5 papers
Simulate, Refocus and Ensemble: An Attention-Refocusing Scheme for Domain Generalization
Ziyi Wang, Zhi Gao, Jin Chen +3
Domain generalization (DG) aims to learn a model from source domains and apply it to unseen target domains with out-of-distribution data. Owing to CLIP's strong ability to encode s…
VUDG: A Dataset for Video Understanding Domain Generalization
Ziyi Wang, Zhi Gao, Boxuan Yu +5
Video understanding has made remarkable progress in recent years, largely driven by advances in deep models and the availability of large-scale annotated datasets. However, existin…
Meta-causal Learning for Single Domain Generalization
Jin Chen, Zhi Gao, Xinxiao Wu +1
Single domain generalization aims to learn a model from a single training domain (source domain) and apply it to multiple unseen test domains (target domains). Existing methods foc…
Bootstrap Generalization Ability from Loss Landscape Perspective
Huanran Chen, Shitong Shao, Ziyi Wang +4
Domain generalization aims to learn a model that can generalize well on the unseen test dataset, i.e., out-of-distribution data, which has different distribution from the training…
Domain Adversarial Reinforcement Learning for Partial Domain Adaptation
Jin Chen, Xinxiao Wu, Lixin Duan +1
Partial domain adaptation aims to transfer knowledge from a label-rich source domain to a label-scarce target domain which relaxes the fully shared label space assumption across di…