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Vision Transformers for Dense Prediction

Vision Transformers for Dense Prediction

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of more than 28% when compared to the top-performing fully-convolutional network for this task. The architecture can also be fine-tuned to small monocular depth prediction datasets, such as NYUv2 [37] and KITTI [15], where it also sets the new state of the art. We provide further evidence of the strong performance of DPT using experiments on se-

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