MNN: Mixed Nearest Neighbors for Self-Supervised Learning

This is an PyTorch implementation of MNN proposed by our paper MNN: Mixed Nearest-Neighbors for Self-Supervised Learning. If you find this repo useful, welcome 🌟🌟🌟✨.

Requirements

To install requirements:

pip install -r requirements.txt

Training and Evaluation

(You need to create the directory './pretrain_output' and './linear_eval_output')

The command line for training and evaluation is in scripts.sh

Pre-trained Models

You can download pretrained models here:

• this link trained on three datasets.
• Download and place in the "./checkpoints" directory

Results

Our model achieves the following performance:

Image Classification on four datasets

-	CIFAR-10	CIFAR-100	STL-10	Tiny ImageNet
MSF	89.94	59.94	88.05	42.68
MNN(Ours)	91.47	67.56	91.61	50.70

Contributors and Contact

📋 If there are any questions, feel free to contact with the authors.