Vision Transformers for Dense Prediction
Paper
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2103.13413
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Published
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1
DPT 3.0 (MiDaS) models, leveraging ViT and ViT-hybrid backbones
Note We introduce dense vision transformers, an architecture that leverages vision transformers in place of convolutional networks as a backbone for dense prediction tasks. We assemble tokens from various stages of the vision transformer into image-like representations at various resolutions and progressively combine them into full-resolution predictions using a convolutional decoder.
Note This model leverages a Vision Transformer (ViT) backbone for monocular depth estimation.
Note This model leverages a hybrid Vision Transformer (ViT-hybrid) backbone for monocular depth estimation.