Python MAE-priv Resources

Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training [Arxiv] VideoMAE: Masked Autoencoders are Data-Efficient Learne

ConvMAE ConvMAE: Masked Convolution Meets Masked Autoencoders Peng Gao1, Teli Ma1, Hongsheng Li2, Jifeng Dai3, Yu Qiao1, 1 Shanghai AI Laboratory, 2 M

ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation

Masked Autoencoders in PyTorch A simple, unofficial implementation of MAE (Masked Autoencoders are Scalable Vision Learners) using pytorch-lightning.

Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @

Masked Auto-Encoder (MAE) Pytorch implementation of Masked Auto-Encoder: Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, Ross Girshick

546 Final Project: Masked Autoencoder Haoran Tang, Qirui Wu 1. Training To train the network, please run mae_pretraining.py. Please modify folder path

Self-Supervised Learning Features self_supervised offers features like modular framework support for multi-gpu training using PyTorch Lightning easy t

mae-repo PyTorch re-implememtation of "masked autoencoders are scalable vision learners". In this repo, it heavily borrows codes from codebase https:/

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

An pytorch implementation of Masked Autoencoders Are Scalable Vision Learners This is a coarse version for MAE, only make the pretrain model, the fine

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners This repository is built upon BEiT, thanks very much! Now, we on

UV-matrix-decompostion-with-kfold UV matrix decompostion using movielens dataset upload the 'ratings.dat' file install the following python libraries