Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers

CVPR 2019 Jingwen HeChao DongYu Qiao

In image restoration tasks, like denoising and super resolution, continual modulation of restoration levels is of great importance for real-world applications, but has failed most of existing deep learning based image restoration methods. Learning from discrete and fixed restoration levels, deep models cannot be easily generalized to data of continuous and unseen levels... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Color Image Denoising CBSD68 sigma15 AdaFM-Net PSNR 34.1 # 1
Color Image Denoising CBSD68 sigma75 AdaFM-Net PSNR 26.35 # 1
Image Super-Resolution Set5 - 3x upscaling AdaFM-Net PSNR 34.34 # 4
Image Super-Resolution Set5 - 4x upscaling AdaFM-Net PSNR 32.13 # 15

Methods used in the Paper


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