Self-promoted supervision for few-shot transformer

• Main Authors: DONG, Bowen, ZHOU, Pan, YAN, Shuicheng, ZUO, Wangmeng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: few-shot learning; location-specific supervision; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8984; https://ink.library.smu.edu.sg/context/sis_research/article/9987/viewcontent/2022_ECCV_few_shot__1_.pdf
• Institution: Singapore Management University

The few-shot learning ability of vision transformers (ViTs) is rarely investigated though heavily desired. In this work, we empirically find that with the same few-shot learning frameworks, e.g. MetaBaseline, replacing the widely used CNN feature extractor with a ViT model often severely impairs few...