Improving tail-class representation with centroid contrastive learning

• المؤلفون الرئيسيون: Tiong, Anthony Meng Huat, Li, Junnan, Lin, Guosheng, Li, Boyang, Xiong, Caiming, Hoi, Steven C. H.
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Imbalanced Learning; Contrastive Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/172214
• المؤسسة: Nanyang Technological University

In vision domain, large-scale natural datasets typically exhibit long-tailed distribution which has large class imbalance between head and tail classes. This distribution poses difficulty in learning good representations for tail classes. Recent developments have shown good long-tailed model can be...