1 code implementation • 5 Oct 2020 • Benjin Zhu, Junqiang Huang, Zeming Li, Xiangyu Zhang, Jian Sun
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 framework.
1 code implementation • 30 Jul 2022 • Junqiang Huang, Xiangwen Kong, Xiangyu Zhang
We focus on better understanding the critical factors of augmentation-invariant representation learning.
no code implementations • ICCV 2023 • Junqiang Huang, Zichao Guo
We present a simple but effective pixel-level self-supervised distillation framework friendly to dense prediction tasks.
no code implementations • 22 Nov 2023 • Ge Luo, Junqiang Huang, Manman Zhang, Zhenxing Qian, Sheng Li, Xinpeng Zhang
In various fine-tune scenarios and against watermark attack methods, our research confirms that analyzing the distribution of watermarks in artificially generated images reliably detects unauthorized mimicry.