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Image Super Resolution On Set5 4X Upscaling

Metrics

PSNR
SSIM

Results

Performance results of various models on this benchmark

Model Name
PSNR
SSIM
Paper TitleRepository
MaIR+33.140.9058MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration-
SRCNN30.490.8628Image Super-Resolution Using Deep Convolutional Networks-
CPAT+33.240.9071Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
ML-CrAIST32.360.8984ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer-
SRGAN29.40.8472Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network-
EDSR32.460.8968Enhanced Deep Residual Networks for Single Image Super-Resolution-
MaIR32.930.9045MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration-
ML-CrAIST-Li32.150.8962ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer-
CPAT33.190.9069Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
HAT-L33.300.9083Activating More Pixels in Image Super-Resolution Transformer-
Hi-IR-L33.220.9103Hierarchical Information Flow for Generalized Efficient Image Restoration-
HMA†33.380.9089HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution-
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Image Super Resolution On Set5 4X Upscaling | SOTA | HyperAI