Revisiting local descriptor for improved few-shot classification

• Main Authors: HE, Jun, HONG, Richang, LIU, Xueliang, XU, Mingliang, SUN, Qianru
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: few-shot learning; image classification; visual recognition; meta-learning; attention networks; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/7558; https://ink.library.smu.edu.sg/context/sis_research/article/8561/viewcontent/dcap.pdf
• Institution: Singapore Management University

Few-shot classification studies the problem of quickly adapting a deep learner to understanding novel classes based on few support images. In this context, recent research efforts have been aimed at designing more and more complex classifiers that measure similarities between query and support image...