[D] Why is ViT more commonly used than SWIN?

I'm still reading around but most every Computer Vision paper I read uses ViT as their backbone instead of SWIN or other similar architectures but why?

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The ViT paper had to pre-train their model on the 303M image JFT dataset to beat earlier convolutional models on ImageNet whereas SWIN achieves better performance without any pre-training. I imagine SWIN would achieve comparable, if not higher performance on ImageNet if it was pre-trained the same way though admittedly I haven't seen …

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