rashmi-rb-333 / Vision-Transformer-Keras-Tensorflow-Pytorch-Examples

Tensorflow implementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformer

Vision-Transformer Keras Tensorflow Pytorch Examples

Tensorflow implementation of the Vision Transformer (ViT) presented in An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, where the authors show that Transformers applied directly to image patches and pre-trained on large datasets work really well on image classification.

Official Paper	Official Code	Article Step By Step
Download	Code	Article

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Vision TransformerDownload PDF.

Collection of Vision Transformer Code

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Sr No	Name	Link
1.	ViT Pytorch (1.9K) ⭐	https://github.com/lucidrains/vit-pytorch
2.	Google Vit Code(1.3K) ⭐	https://github.com/google-research/vision_transformer
3.	JeonWorld(161) ⭐	https://github.com/jeonsworld/ViT-pytorch
4.	Vit Tensorflow2	https://github.com/ashishpatel26/Vision-Transformer-Keras-Tensorflow-Pytorch-Examples/blob/main/Vision_Transformer_with_tf2.ipynb
5.	Vision Transformer Pytorch(80)⭐	https://github.com/asyml/vision-transformer-pytorch
6.	Pretrained Vision Transformer (70)⭐	https://github.com/lukemelas/PyTorch-Pretrained-ViT
7.	Vision Transformer TF2(49) ⭐	https://github.com/kamalkraj/Vision-Transformer
8.	Vision Transformer Tensorflow(62) ⭐	https://github.com/emla2805/vision-transformer
9.	Vision Transformer with Control Activation Map(40) ⭐	https://github.com/jacobgil/vit-explain
10.	Vision Transformer Keras(32)⭐	https://github.com/tuvovan/Vision_Transformer_Keras
11.	Vision Transformer (20) ⭐	https://github.com/tahmid0007/VisionTransformer
12.	ViT Keras (12) ⭐	https://github.com/faustomorales/vit-keras
13.	VIT Pytorch(9) ⭐	https://github.com/tczhangzhi/VisionTransformer-Pytorch
14.	ViT Tensorflow 2 (6)⭐	https://github.com/soumik12345/Vision-Transformer

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Citation

@inproceedings{
    anonymous2021an,
    title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
    author={Anonymous},
    booktitle={Submitted to International Conference on Learning Representations},
    year={2021},
    url={https://openreview.net/forum?id=YicbFdNTTy},
    note={under review}
}

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Thanks for Reading

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