This is an unofficial implementation of Moco v1 (Momentum Contrast for Unsupervised Visual Representation Learning, CVPR 2020.) and Moco v2 (Improved Baselines with Momentum Contrastive Learning).
- python >= 3.6
- tensorflow >= 2.2 (2.2 and 2.3)
For training moco v1,
python main.py \
--task v1 \
--weight_decay 0.0001 \
--brightness 0.4 \
--contrast 0.4 \
--saturation 0.4 \
--hue 0.4 \
--lr_mode exponential \
--lr_interval 120,160 \
--data_path /path/of/your/data \
--gpus gpu id(s) which will be used
or moco v2,
python main.py \
--task v2 \
--weight_decay 0.0001 \
--mlp \
--brightness 0.4 \
--contrast 0.4 \
--saturation 0.4 \
--hue 0.1 \
--lr_mode cosine \
--data_path /path/of/your/data \
--gpus gpu id(s) which will be used
For training linear classification,
python main.py \
--task lincls \
--batch_size 256 \
--epochs 100 \
--lr 30 \
--lr_mode constant \
--data_path /path/of/your/data \
--snapshot /path/of/checkpoint \
--gpus gpu id(s) which will be used
Our model achieves the following performance on :
| Model | batch | Accuracy (paper) | Accuracy (ours) |
|---|---|---|---|
| ResNet50 (200 epochs) | 256 | 60.6 | - |
| Model | batch | Accuracy (paper) | Accuracy (ours) |
|---|---|---|---|
| ResNet50 (200 epochs) | 256 | 67.5 | - |
| ResNet50 (800 epochs) | 256 | 71.1 | - |
@Article{he2019moco,
author = {Kaiming He and Haoqi Fan and Yuxin Wu and Saining Xie and Ross Girshick},
title = {Momentum Contrast for Unsupervised Visual Representation Learning},
journal = {arXiv preprint arXiv:1911.05722},
year = {2019},
}
@Article{chen2020mocov2,
author = {Xinlei Chen and Haoqi Fan and Ross Girshick and Kaiming He},
title = {Improved Baselines with Momentum Contrastive Learning},
journal = {arXiv preprint arXiv:2003.04297},
year = {2020},
}