Image Dehazing On Sots Indoor

PSNR

SSIM

평가 결과

이 벤치마크에서 각 모델의 성능 결과

			Paper Title
ConvIR	42.72	0.997	Revitalizing Convolutional Network for Image Restoration
MixDehazeNet	42.62	0.997	MixDehazeNet : Mix Structure Block For Image Dehazing Network
C2PNet	42.56	0.9954	Curricular Contrastive Regularization for Physics-aware Single Image Dehazing
FSNet	42.45	0.997	Image Restoration via Frequency Selection
ChaIR	41.95	0.997	Exploring the potential of channel interactions for image restoration
DSANet	41.36	0.997	Dual-domain strip attention for image restoration
gUNet-D	41.34	0.996	Rethinking Performance Gains in Image Dehazing Networks
DEA-Net-CR	41.31	0.9945	DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention
SFNet	41.24	0.996	Selective Frequency Network for Image Restoration
IRNeXt	41.21	0.996	IRNeXt: Rethinking Convolutional Network Design for Image Restoration
FocalNet	40.82	0.996	Focal Network for Image Restoration
OKNet	40.79	0.996	Omni-Kernel Network for Image Restoration
SANet	40.40	0.996	Strip Attention for Image Restoration
DehazeFormer-L	40.05	0.996	Vision Transformers for Single Image Dehazing
MaIR	39.45	0.997	MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
HDM	38.56	0.991	Learning Hierarchical Dynamics with Spatial Adjacency for Image Enhancement
PMNet	38.41	0.99	Perceiving and Modeling Density is All You Need for Image Dehazing
MAXIM-2S	38.11	-	MAXIM: Multi-Axis MLP for Image Processing
AECR-Net	37.17	0.990	Contrastive Learning for Compact Single Image Dehazing
U2-Former	36.42	0.988	U2-Former: A Nested U-shaped Transformer for Image Restoration

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