Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

Last update: Nov 25, 2022

Overview

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification

This is an unofficial PyTorch implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification .

Usage :

import torch
from crossvit import CrossViT

img = torch.ones([1, 3, 224, 224])
    
model = CrossViT(image_size = 224, channels = 3, num_classes = 100)
out = model(img)

print("Shape of out :", out.shape)      # [B, num_classes]

Citation

@misc{chen2021crossvit,
      title={CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification}, 
      author={Chun-Fu Chen and Quanfu Fan and Rameswar Panda},
      year={2021},
      eprint={2103.14899},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Acknowledgement

Base ViT code is borrowed from @lucidrains repo : https://github.com/lucidrains/vit-pytorch

Owner

Rishikesh (ऋषिकेश)

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Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

Related tags

Overview

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification

Usage :

Citation

Acknowledgement

Owner

Rishikesh (ऋषिकेश)

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