Residual Dense Network for Image Restoration

25 Dec 2018Yulun ZhangYapeng TianYu KongBineng ZhongYun Fu

Convolutional neural network has recently achieved great success for image restoration (IR) and also offered hierarchical features. However, most deep CNN based IR models do not make full use of the hierarchical features from the original low-quality images, thereby achieving relatively-low performance... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Image Denoising BSD68 sigma10 Residual Dense Network + PSNR 36.49 # 1
Image Denoising BSD68 sigma30 Residual Dense Network + PSNR 30.70 # 1
Image Denoising BSD68 sigma50 RDN+ PSNR 26.43 # 3
Image Denoising BSD68 sigma70 Residual Dense Network + PSNR 26.88 # 1
Image Denoising Urban100 sigma30 Residual Dense Network + PSNR 31.78 # 1
Image Denoising Urban100 sigma50 Residual Dense Network + PSNR 29.38 # 1
Image Denoising Urban100 sigma70 Residual Dense Network + PSNR 27.74 # 1