| ---
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| license: apache-2.0
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| ---
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| ## FDViT: Improve the Hierarchical Architecture of Vision Transformer (ICCV 2023)
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| **Yixing Xu, Chao Li, Dong Li, Xiao Sheng, Fan Jiang, Lu Tian, Ashish Sirasao** | [Paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Xu_FDViT_Improve_the_Hierarchical_Architecture_of_Vision_Transformer_ICCV_2023_paper.pdf)
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| Advanced Micro Devices, Inc.
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|
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| ---
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|
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| ## Dependancies
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|
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| ```bash
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| torch == 1.13.1
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| torchvision == 0.14.1
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| timm == 0.6.12
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| einops == 0.6.1
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| ```
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| ## Model performance
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| The image classification results of FDViT models on ImageNet dataset are shown in the following table.
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| |Model|Parameters (M)|FLOPs(G)|Top-1 Accuracy (%)|
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| |-|-|-|-|
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| |FDViT-Ti|4.6|0.6|73.74|
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| |FDViT-S|21.6|2.8|81.45|
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| |FDViT-B|68.1|11.9|82.39|
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|
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| ## Model Usage
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|
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| ```bash
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| from transformers import AutoModelForImageClassification
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| import torch
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| model = AutoModelForImageClassification.from_pretrained("FDViT_b", trust_remote_code=True)
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| model.eval()
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| inp = torch.ones(1,3,224,224)
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| out = model(inp)
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| ```
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| ## Citation
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|
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| ```
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| @inproceedings{xu2023fdvit,
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| title={FDViT: Improve the Hierarchical Architecture of Vision Transformer},
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| author={Xu, Yixing and Li, Chao and Li, Dong and Sheng, Xiao and Jiang, Fan and Tian, Lu and Sirasao, Ashish},
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| booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
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| pages={5950--5960},
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| year={2023}
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| }
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| ```
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|
