Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning. (arXiv:2205.09995v1 [cs.CV])

Learning with little data is challenging but often inevitable in various
application scenarios where the labeled data is limited and costly. Recently,
few-shot learning (FSL) gained increasing attention because of its
generalizability of prior knowledge to new tasks that contain only a few
samples. However, for data-intensive models such as vision transformer (ViT),
current fine-tuning based FSL approaches are inefficient in knowledge
generalization and thus degenerate the downstream task performances. In this
paper, we propose a novel mask-guided vision transformer …

arxiv cv few-shot learning learning transformer vision