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

Related tags

Deep Learningclassifiercomputer-visiontransformerspytorchimage-classificationvision-transformers
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

Owner
Rishikesh (ऋषिकेश)
Deep Learning/ AI Researcher | Open Source enthusiast | Text to Speech | Speech Synthesis | Generative Models | Object detection | Language Understanding
Rishikesh (ऋषिकेश)
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