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 |