Vision Transformer-based Adversarial Domain Adaptation

arXiv:2404.15817v1 Announce Type: cross
Abstract: Unsupervised domain adaptation (UDA) aims to transfer knowledge from a labeled source domain to an unlabeled target domain. The most recent UDA methods always resort to adversarial training to yield state-of-the-art results and a dominant number of existing UDA methods employ convolutional neural networks (CNNs) as feature extractors to learn domain invariant features. Vision transformer (ViT) has attracted tremendous attention since its emergence and has been widely used in various computer vision tasks, such as …

adversarial arxiv cs.cv cs.lg domain domain adaptation transformer type vision