TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Color Image Denoising	BSD68 sigma15	RIDNet	PSNR	34.01	# 1
Grayscale Image Denoising	BSD68 sigma15	RIDNet	PSNR	31.81	# 4
Grayscale Image Denoising	BSD68 sigma25	RIDNet	PSNR	29.34	# 4
Color Image Denoising	BSD68 sigma25	RIDNet	PSNR	31.37	# 1
Grayscale Image Denoising	BSD68 sigma50	RIDNet	PSNR	26.4	# 4
Color Image Denoising	CBSD68 sigma50	RIDNet	PSNR	28.14	# 2
Color Image Denoising	Darmstadt Noise Dataset	RIDNet (blind)	PSNR (sRGB)	39.23	# 3
Color Image Denoising	Darmstadt Noise Dataset	RIDNet (blind)	SSIM (sRGB)	0.9526	# 3
Image Denoising	DND	RIDNet	PSNR (sRGB)	39.26	# 7
Image Denoising	DND	RIDNet	SSIM (sRGB)	0.953	# 4
Image Denoising	SIDD	RIDNet	PSNR (sRGB)	38.71	# 7
Image Denoising	SIDD	RIDNet	SSIM (sRGB)	0.951	# 7

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Real Image Denoising with Feature Attention

ICCV 2019 • Saeed Anwar • Nick Barnes

Deep convolutional neural networks perform better on images containing spatially invariant noise (synthetic noise); however, their performance is limited on real-noisy photographs and requires multiple stage network modeling. To advance the practicability of denoising algorithms, this paper proposes a novel single-stage blind real image denoising network (RIDNet) by employing a modular architecture... (read more)

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saeed-anwar/RIDNet

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COLOR IMAGE DENOISING

DENOISING

IMAGE DENOISING

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BSD

DIV2K

Set12

SIDD CBSD68

DND

Results from the Paper

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Ranked #1 on Color Image Denoising on BSD68 sigma25

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TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	BENCHMARK
Color Image Denoising	BSD68 sigma15	RIDNet	PSNR	34.01	# 1	Compare
Grayscale Image Denoising	BSD68 sigma15	RIDNet	PSNR	31.81	# 4	Compare
Grayscale Image Denoising	BSD68 sigma25	RIDNet	PSNR	29.34	# 4	Compare
Color Image Denoising	BSD68 sigma25	RIDNet	PSNR	31.37	# 1	Compare
Grayscale Image Denoising	BSD68 sigma50	RIDNet	PSNR	26.4	# 4	Compare
Color Image Denoising	CBSD68 sigma50	RIDNet	PSNR	28.14	# 2	Compare
Color Image Denoising	Darmstadt Noise Dataset	RIDNet (blind)	PSNR (sRGB)	39.23	# 3	Compare
Color Image Denoising	Darmstadt Noise Dataset	RIDNet (blind)	SSIM (sRGB)	0.9526	# 3	Compare
Image Denoising	DND	RIDNet	PSNR (sRGB)	39.26	# 7	Compare
Image Denoising	DND	RIDNet	SSIM (sRGB)	0.953	# 4	Compare
Image Denoising	SIDD	RIDNet	PSNR (sRGB)	38.71	# 7	Compare
Image Denoising	SIDD	RIDNet	SSIM (sRGB)	0.951	# 7	Compare

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