MAE
[NeurIPS2022] Official implementation of the paper 'Green Hierarchical Vision Transformer for Masked Image Modeling'.
A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).
(ICLR 2023) Official PyTorch implementation of "What Do Self-Supervised Vision Transformers Learn?"
Official Implementation of Attentive Mask CLIP (ICCV2023, https://arxiv.org/abs/2212.08653)
CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet
Code release for SLIP Self-supervision meets Language-Image Pre-training
MultiMAE: Multi-modal Multi-task Masked Autoencoders, ECCV 2022
[ECCV 2024] PyTorch implementation of CropMAE, introduced in "Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders"