2 papers
cs.CV2022
Revisiting the Critical Factors of Augmentation-Invariant Representation Learning
Junqiang Huang, Xiangwen Kong, Xiangyu Zhang
We focus on better understanding the critical factors of augmentation-invariant representation learning. We revisit MoCo v2 and BYOL and try to prove the authenticity of the follow…
cs.CV2020
EqCo: Equivalent Rules for Self-supervised Contrastive Learning
Benjin Zhu, Junqiang Huang, Zeming Li +2
In this paper, we propose EqCo (Equivalent Rules for Contrastive Learning) to make self-supervised learning irrelevant to the number of negative samples in the contrastive learning…