Image Super Resolution On Bsd100 2X Upscaling

评估指标

PSNR

评测结果

各个模型在此基准测试上的表现结果

模型名称	PSNR	Paper Title	Repository
MWCNN	32.23	Multi-level Wavelet-CNN for Image Restoration
SwinFIR	32.64	SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
Hi-IR-L	32.77	Hierarchical Information Flow for Generalized Efficient Image Restoration	-
CARN [[Ahn et al.2018]]	32.09	Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network
DnCNN-3	31.9	Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
HAT-L	32.74	Activating More Pixels in Image Super-Resolution Transformer
WaveMixSR-V2	33.12	WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency
FALSR-A	32.12	Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
RED30	31.99	Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
IMDN	32.19	Lightweight Image Super-Resolution with Information Multi-distillation Network
CPAT	32.64	Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution	-
DRCT-L	32.90	DRCT: Saving Image Super-resolution away from Information Bottleneck
LTE	32.44	Local Texture Estimator for Implicit Representation Function
HAT_FIR	32.71	SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
SwinOIR	32.34	Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
SRFBN	32.29	Feedback Network for Image Super-Resolution
CSNLN	32.4	Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
IPT	32.48	Pre-Trained Image Processing Transformer
FSRCNN [[Dong et al.2016]]	31.53	Accelerating the Super-Resolution Convolutional Neural Network
HMA†	32.79	HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution

0 of 30 row(s) selected.