Support new self-supervised method BEiT with ViT-Base on ImageNet-1K, and fix bugs of CAE, MaskFeat, and SimMIM in Dataset, Model, and Head. Note that we added HOG feature implementation borrowed from the original repo for MaskFeat.
Support new backbone architecture DeiT-3 and provide configs.
Update pre-training and fine-tuning config files, and documents for the relevant masked image modeling (MIM) methods (BEiT, MaskFeat, CAE, and A2MIM).
Support Grad-CAM visualization tools vis_cam.py of supported architectures.
Updating documents:
Update the template and add the latest paper lists of mixup and MIM methods in Awesome Mixups and Awesome MIM.
Updating features:
Dataset
,Model
, andHead
. Note that we addedHOG
feature implementation borrowed from the original repo for MaskFeat.Updating documents:
tools
.