103 citations · 145 across the 8 of their papers we have counts for
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cs.LG2023★ 1 cited
Universal Domain Adaptation from Foundation Models: A Baseline Study
Bin Deng, Kui Jia
Foundation models (e.g., CLIP or DINOv2) have shown their impressive learning and transfer capabilities in a wide range of visual tasks, by training on a large corpus of data and a…
cs.CV2023★ 4 cited
Adversarial Style Augmentation for Domain Generalization
Yabin Zhang, Bin Deng, Ruihuang Li +2
It is well-known that the performance of well-trained deep neural networks may degrade significantly when they are applied to data with even slightly shifted distributions. Recent…