Baofeng Tan

Prototype-based Contrastive Learning with Stage-wise Progressive Augmentation for Self-Supervised Fine-Grained Learning

In this paper, we mitigate the problem of Self-Supervised Learning (SSL) for fine-grained representation learning, aimed at distinguishing subtle differences within highly similar subordinate categories. Our preliminary analysis shows that SSL, especially the multi-stage alignment strategy, performs…