Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning

This repository is the official implementation of CARE paper.

Updates

• (09/10/2021) Our paper is accepted by NeurIPS 2021.
• (14/10/2021) Our code is available for ssl pretraining and image classification evaluation.

Comming

• Provide resnet_50(100e) models and logs.
• Complete the pretrained models and logs.

Requirements

To install requirements:

conda create -n care python=3.6

conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=10.1

 
 

 
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