Nov 14, 2022 · We are the first to propose a pixel augmentation method with a pixel granularity for enhancing unsupervised pixel-wise contrastive learning.

Contrastive learning (CL) is a form of self-supervised learning and has been widely used for various tasks. Different from widely studied instance-level ...

We are the first to propose a pixel augmentation method with a pixel granularity for enhancing unsupervised pixel-wise contrastive learning.

To the best of our knowledge, we are the first to propose a pixel augmentation method with a pixel granularity for enhancing unsupervised pixel-wise contrastive ...

This work proposes a novel uncertainty-guided pixel contrastive learning method for semi-supervised medical image segmentation and proposes that the ...

Information-guided pixel augmentation for pixel-wise contrastive learning. Q Quan, Q Yao, J Li. arXiv preprint arXiv:2211.07118, 2022. 5, 2022 ; UOD: Universal ...

We present a simple but effective pixel-level self- supervised distillation framework friendly to dense predic- tion tasks. Our method, called Pixel-Wise ...

Extensive experiments validate that our information-guided pixel augmentation strategy succeeds in encoding more discriminative representations and surpassing ...

To the best of our knowledge, we are the first to propose a pixel augmentation method with a pixel granularity for enhancing unsupervised pixel-wise contrastive ...

Pixel/region-level self-supervised learning aims to learn competitive representations specialized for dense prediction tasks. Following the philosophy of ...