Hi,

Thanks for maintaining this repository. Appreciate your efforts.

Please add our paper "Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation" that provides a novel way
to learn powerful representations in Semi-Supervised Setting using Contrastive Learning for images.
arXiv: https://arxiv.org/abs/2106.06801

The paper is accepted at MICCAI 2021.

Many thanks for your kind sharing! Would you please help us to share our CVPR 2024 paper about Contrastive SSL? Thank you very much!

Paper title: VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis
Publication: CVPR 2024
Paper link: https://arxiv.org/abs/2402.17300
Code link: https://github.com/Luffy03/VoCo

We appreciate your effort on the maintenance of this awesome repository.
We would like to recommend our recent research works on contrastive learning, which achieve state-of-the-art performance on popular benchmarks.
The papers are listed as follows:
Inter-Instance Similarity Modeling for Contrastive Learning
Asymmetric Patch Sampling for Contrastive Learning
Both of them provides open source code and trained model weights at Github, which can be found at following links:
https://github.com/visresearch/patchmix
https://github.com/visresearch/aps

Thanks!