masked-image-modeling

OpenMMLab Pre-training Toolbox and Benchmark

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling"

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark

ConvMAE: Masked Convolution Meets Masked Autoencoders

[ICCV 2023] You Only Look at One Partial Sequence

[Survey] Masked Modeling for Self-supervised Representation Learning on Vision and Beyond (https://arxiv.org/abs/2401.00897)

Official Codes for "Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality"

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

[NeurIPS2022] Official implementation of the paper 'Green Hierarchical Vision Transformer for Masked Image Modeling'.

MixMIM: Mixed and Masked Image Modeling for Efficient Visual Representation Learning

Official PyTorch implementation of MOOD series: (1) MOODv1: Rethinking Out-of-distributionDetection: Masked Image Modeling Is All You Need. (2) MOODv2: Masked Image Modeling for Out-of-Distribution Detection.

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

PyTorch code for MUST

[CVPR'23 & TPAMI'25] Hard Patches Mining for Masked Image Modeling

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

[ICLR2024] Exploring Target Representations for Masked Autoencoders

[NIPS'23] Official Code of the paper "Cross-Scale MAE: A Tale of Multi-Scale Exploitation in Remote Sensing"

PyTorch reimplementation of "A simple, efficient and scalable contrastive masked autoencoder for learning visual representations".