Maobin Tang

End-to-End Knowledge Distillation for Unsupervised Domain Adaptation with Large Vision-language Models

Knowledge distillation based on large vision-language models (VLMs) has recently emerged as a significant solution to transfer knowledge from the source domain to the target domain in unsupervised domain adaptation (UDA) tasks. However, existing methods employ a two-stage training pipeline, which no