awesome-MIM

Reading list for research topics in Masked Image Modeling(MIM).

We list the most popular methods for MIM, if I missed something, please submit a request. (Note: We show the date of the first version of Arxiv here. But the link of paper may be not the early version.)

Self-supervied Vision Transformers as backbone models.

Date	Method	Conference	Title	Code
2021-06-14	BeiT	ICLR 2022(Oral)	BEiT: BERT Pre-Training of Image Transformers	BeiT
2021-11-11	MAE	Arxiv 2021	Masked Autoencoders Are Scalable Vision Learners	MAE
2021-11-15	iBoT	Arxiv 2021	iBOT: Image BERT Pre-Training with Online Tokenizer	iBoT
2021-11-18	SimMIM	Arxiv 2021	SimMIM: A Simple Framework for Masked Image Modeling	SimMIM
2021-12-16	MaskFeat	Arxiv 2021	Masked Feature Prediction for Self-Supervised Visual Pre-Training	None
2021-12-20	SplitMask	Arxiv 2021	Are Large-scale Datasets Necessary for Self-Supervised Pre-training?	None
2022-01-31	ADIOS	Arxiv 2022	Adversarial Masking for Self-Supervised Learning	None
2022-02-07	CAE	Arxiv 2022	Context Autoencoder for Self-Supervised Representation Learning	None
2022-02-07	CIM	Arxiv 2022	Corrupted Image Modeling for Self-Supervised Visual Pre-Training	None

Reading list for research topics in Masked Image Modeling

Related tags

Overview

awesome-MIM

Self-supervied Vision Transformers as backbone models.

Owner

ligang

Pytorch implementation of the paper DocEnTr: An End-to-End Document Image Enhancement Transformer.

Implementation of Multistream Transformers in Pytorch

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper submitted to KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition.

Boundary-preserving Mask R-CNN (ECCV 2020)

JupyterLite demo deployed to GitHub Pages 🚀

Residual Pathway Priors for Soft Equivariance Constraints

Tree-based Search Graph for Approximate Nearest Neighbor Search

For visualizing the dair-v2x-i dataset

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)

A python comtrade load library accelerated by go

AOT (Associating Objects with Transformers) in PyTorch

Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

CT-Net: Channel Tensorization Network for Video Classification

最新版本yolov5+deepsort目标检测和追踪，支持5.0版本可训练自己数据集

Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

A framework for analyzing computer vision models with simulated data

Automated Evidence Collection for Fake News Detection

ROS Basics and TurtleSim

RADIal is available now! Check the download section

AI Toolkit for Healthcare Imaging