MoCo v2
MoCo v2
**MoCo v2** is an improved version of the [Momentum Contrast](https://paperswithcode.com/method/moco) self-supervised learning algorithm. Motivated by the findings presented in the [SimCLR](https://paperswithcode.com/method/simclr) paper, authors:

- Replace the 1-layer fully connected layer with a 2-layer MLP head with [ReLU](https://paperswithcode.com/method/relu) for the unsupervised training stage.
- Include blur augmentation.
- Use cosine learning rate schedule.

These modifications enable MoCo to outperform the state-of-the-art SimCLR with a smaller batch size and fewer epochs.
Improved Baselines with Momentum Contrastive Learning
https://paperswithcode.com/paper/improved-baselines-with-momentum-contrastive
Improved Baselines with Momentum Contrastive Learning