2 citations · 9 across the 6 of their papers we have counts for
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cs.CV2024★ 1 cited
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context
Jing Wang, Wonho Bae, Jiahong Chen +3
Source-free domain adaptation (SFDA) involves adapting a model originally trained using a labeled dataset ({\em source domain}) to perform effectively on an unlabeled dataset ({\em…
cs.LG2024★ 2 cited
Contrastive Adversarial Training for Unsupervised Domain Adaptation
Jiahong Chen, Zhilin Zhang, Lucy Li +2
Domain adversarial training has shown its effective capability for finding domain invariant feature representations and been successfully adopted for various domain adaptation task…