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Restormer: Efficient Transformer for High-Resolution Image Restoration was published in CVPR 2022, which introduced a new Vision Transformer based architecture for Image Restoration tasks like Deraining, Motion Deblurring, Defocus Deblurring and Denoising. It reduced the time complexity of Self Attention in Vision Transformers from O(n2) to O(n) by introducing Multi-Dconv Head Transposed Attention. It also introduced Gated-Dconv Feed-Forward Network.
@manyana72 and I would like to add this model to Huggingface.
Model description
Restormer: Efficient Transformer for High-Resolution Image Restoration was published in CVPR 2022, which introduced a new Vision Transformer based architecture for Image Restoration tasks like Deraining, Motion Deblurring, Defocus Deblurring and Denoising. It reduced the time complexity of Self Attention in Vision Transformers from O(n2) to O(n) by introducing Multi-Dconv Head Transposed Attention. It also introduced Gated-Dconv Feed-Forward Network.
@manyana72 and I would like to add this model to Huggingface.
cc: @NielsRogge
Open source status
Provide useful links for the implementation
Paper, Code Implementation and pretrained model weights
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