Image Super Resolution On Set14 2X Upscaling

评估指标

PSNR

SSIM

评测结果

各个模型在此基准测试上的表现结果

			Paper Title	Repository
DRCT-L	35.36	0.9302	DRCT: Saving Image Super-resolution away from Information Bottleneck
HMA†	35.33	0.9297	HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
HAT-L	35.29	0.9293	Activating More Pixels in Image Super-Resolution Transformer
Hi-IR-L	35.27	0.9311	Hierarchical Information Flow for Generalized Efficient Image Restoration	-
HAT_FIR	35.17	-	SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
HAT	35.13	0.9282	Activating More Pixels in Image Super-Resolution Transformer
CPAT+	34.97	0.9280	Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution	-
DRCT	34.96	0.9287	DRCT: Saving Image Super-resolution away from Information Bottleneck
SwinFIR	34.93	0.9276	SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
CPAT	34.91	0.9277	Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution	-
MaIR	34.75	0.9268	MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
DRLN+	34.43	0.9247	Densely Residual Laplacian Super-Resolution
CSRCNN	34.34	0.9240	Cascade Convolutional Neural Network for Image Super-Resolution	-
LTE	34.25	-	Local Texture Estimator for Implicit Representation Function
HAN+	34.24	0.9224	Single Image Super-Resolution via a Holistic Attention Network
CSNLN	34.12	0.9223	Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
DBPN-RES-MR64-3	34.09	0.921	Deep Back-Projection Networks for Single Image Super-resolution
SwinOIR	33.97	0.922	Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
SRFBN	33.82	-	Feedback Network for Image Super-Resolution
HBPN	33.78	0.921	Hierarchical Back Projection Network for Image Super-Resolution

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