PyTorch implementation of BYOL: a fantastically simple method for self-supervised image representation learning with SOTA performance.
MIT License
PyTorch implementation of BYOL: a fantastically simple method for self-supervised image representation learning with SOTA performance. Strongly influenced and inspired by this Github repo, but with a few notable differences:
kornia.augmentation.RandomResizedCrop
currently doesn't support this. I'll need to ensure that our implementation is sufficiently performant, so it doesn't inadvertently slow down training.