https://github.com/VILA-Lab/i-mae

i-mae Pytorch Repo
https://github.com/VILA-Lab/i-mae

Last synced: 3 months ago
JSON representation

i-mae Pytorch Repo

• Host: GitHub
• URL: https://github.com/VILA-Lab/i-mae
• Owner: VILA-Lab
• Created: 2022-10-20T18:28:51.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2024-04-06T15:05:18.000Z (7 months ago)
• Last Synced: 2024-07-28T19:19:37.525Z (3 months ago)
• Language: Python
• Size: 38.1 KB
• Stars: 19
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• Awesome-Mixup - [Code

README

        
# A PyTorch Implementation of i-MAE: Linearly Separable Representation in MAE

[Kevin Zhang*](https://kzyz.netlify.com/), [Zhiqiang Shen*](http://zhiqiangshen.com/)

[`Project Page`](https://zhiqiangshen.com/projects/i-mae/)

| [`Paper`](https://arxiv.org/abs/2210.11470)

| [`BibTeX`](#citation)

[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vision-learning-acceleration-lab/i-mae/blob/main/i-MAE_demo.ipynb)

![i-MAE2](https://user-images.githubusercontent.com/52997677/196735725-496592d3-5883-4db4-ba34-04d0a8dab535.svg)

We provide a PyTorch/GPU based implementation of our technical report [i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?

](https://arxiv.org/abs/2210.11470)

### Catalog

- [X] Pretrain demo with Colab

- [X] Pre-training and Fine-tuning code

- [ ] Weights Upload

### Pre-training

The pre-training instruction is in [PRETRAIN.md](https://github.com/facebookresearch/mae/blob/main/PRETRAIN.md).

### Fine-tuning

The fine-tuning instruction is in [FINETUNE.md](https://github.com/facebookresearch/mae/blob/main/FINETUNE.md).

### Visualization demo

Please visit our interactive demo on our [website](https://zhiqiangshen.com/projects/i-mae/), or run our visualization demo with a [Colab notebook](https://colab.research.google.com/github/vision-learning-acceleration-lab/i-mae/blob/main/i-MAE_demo.ipynb) [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vision-learning-acceleration-lab/i-mae/blob/main/i-MAE_demo.ipynb)

### Acknowledgement

This repository is based on [timm](https://github.com/rwightman/pytorch-image-models/tree/master/timm) and [MAE](https://github.com/facebookresearch/mae) repositories.

### License

This project is under the CC-BY-NC 4.0 license. See [LICENSE](LICENSE) for details.

### Citation

If you find this repository helpful, please consider citing our work:

```

@article{zhang2022i-mae,

  title={i-MAE: Are Latent Representations in Masked Autoencoders Linearly Separable?},

  author = {Zhang, Kevin and Shen, Zhiqiang},

  journal={arXiv preprint arXiv:2210.11470},

  year={2022}

}

```