Color Image Denoising On Cbsd68 Sigma50

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Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
IPT	29.39	Pre-Trained Image Processing Transformer
ADL	29.02	Adversarial Distortion Learning for Medical Image Denoising
DMID-d (MMSE)	28.69	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
DMID-d	28.69	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
AKDT	28.68	AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising
Instruct-IPT	28.61	Instruct-IPT: All-in-One Image Processing Transformer via Weight Modulation
Residual Dense Network +	28.34	Residual Dense Network for Image Super-Resolution
RCOT	28.25	Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
RIDNet	28.14	Real Image Denoising with Feature Attention
DnCNN	28.01	Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification
CSCNet	28.00	Rethinking the CSC Model for Natural Images
FFDNet	27.96	FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising
PaCNet	27.93	Patch Craft: Video Denoising by Deep Modeling and Patch Matching
IRCNN	27.86	Learning Deep CNN Denoiser Prior for Image Restoration
Spatial-CNN	27.63	ViDeNN: Deep Blind Video Denoising
DMID-p	26.63	Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
CBUIFD75	26.60	Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
MemNet	26.33	MemNet: A Persistent Memory Network for Image Restoration

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Color Image Denoising On Cbsd68 Sigma50 | SOTA | HyperAI