Color Image Denoising On Mcmaster Sigma50

Metrics

LPIPS

SSIM

Results

Performance results of various models on this benchmark

			Paper Title
DMID-d(MMSE)	0.124	0.9396	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
FFDNet	-	-	FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
Hi-IR	-	-	Hierarchical Information Flow for Generalized Efficient Image Restoration
AKDT	-	-	AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising
KBNet	-	-	KBNet: Kernel Basis Network for Image Restoration
DMID-d	-	-	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
DMID-p	0.092	0.9112	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling

0 of 7 row(s) selected.

Color Image Denoising On Mcmaster Sigma50

Metrics

LPIPS

SSIM

Results

Performance results of various models on this benchmark

			Paper Title
DMID-d(MMSE)	0.124	0.9396	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
FFDNet	-	-	FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
Hi-IR	-	-	Hierarchical Information Flow for Generalized Efficient Image Restoration
AKDT	-	-	AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising
KBNet	-	-	KBNet: Kernel Basis Network for Image Restoration
DMID-d	-	-	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
DMID-p	0.092	0.9112	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling

0 of 7 row(s) selected.

Color Image Denoising On Mcmaster Sigma50 | SOTA | HyperAI