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

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Overview

awesome-MIM

Self-supervied Vision Transformers as backbone models.

Owner

ligang

Code for the bachelors-thesis flaky fault localization

RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch

Self-supervised learning (SSL) is a method of machine learning

Implementation of ConvMixer for "Patches Are All You Need? 🤷"

Pytorch implementation of our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION.

Experiments with differentiable stacks and queues in PyTorch

A Simplied Framework of GAN Inversion

A deep neural networks for images using CNN algorithm.

Pytorch library for seismic data augmentation

Revisting Open World Object Detection

Code to generate datasets used in "How Useful is Self-Supervised Pretraining for Visual Tasks?"

AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation

Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Retrieval.

PINN Burgers - 1D Burgers equation simulated by PINN

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

PAIRED in PyTorch 🔥

Code accompanying the NeurIPS 2021 paper "Generating High-Quality Explanations for Navigation in Partially-Revealed Environments"

Code for our method RePRI for Few-Shot Segmentation. Paper at http://arxiv.org/abs/2012.06166

A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.

YOLOV4运行在嵌入式设备上