Image Super Resolution On Urban100 2X

평가 지표

PSNR

SSIM

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	PSNR	SSIM	Paper Title	Repository
SwinOIR	32.83	0.9353	Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy	-
HMA†	35.24	0.9513	HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution	-
SPBP-L+	32.07	0.9277	Sub-Pixel Back-Projection Network For Lightweight Single Image Super-Resolution	-
FACD	32.878	-	Feature-domain Adaptive Contrastive Distillation for Efficient Single Image Super-Resolution	-
CSNLN	33.25	0.9386	Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining	-
MWCNN	32.3	-	Multi-level Wavelet-CNN for Image Restoration	-
VDSR [[Kim et al.2016a]]	30.76	-	Accurate Image Super-Resolution Using Very Deep Convolutional Networks	-
HAT	34.81	0.9489	Activating More Pixels in Image Super-Resolution Transformer	-
DRCT-L	35.17	0.9516	DRCT: Saving Image Super-resolution away from Information Bottleneck	-
DBPN-RES-MR64-3	32.92	0.935	Deep Back-Projection Networks for Single Image Super-resolution	-
PMRN+	32.78	0.9342	Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution	-
DRLN+	33.54	0.9402	Densely Residual Laplacian Super-Resolution	-
HAT-L	35.09	0.9505	Activating More Pixels in Image Super-Resolution Transformer	-
ML-CrAIST-Li	32.93	0.9361	ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer	-
DRCN [[Kim et al.2016b]]	30.75	-	Deeply-Recursive Convolutional Network for Image Super-Resolution	-
DnCNN-3	30.74	-	Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising	-
SwinFIR	34.57	0.9473	SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution	-
Hi-IR-L	35.16	0.9505	Hierarchical Information Flow for Generalized Efficient Image Restoration	-
ML-CrAIST	33.04	0.937	ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer	-
DRCT	34.54	0.9474	DRCT: Saving Image Super-resolution away from Information Bottleneck	-

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