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Image Super Resolution On Bsd100 3X Upscaling

Metrics

PSNR

Results

Performance results of various models on this benchmark

Paper TitleRepository
Hi-IR-L29.67Hierarchical Information Flow for Generalized Efficient Image Restoration-
HMA†29.66HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
HAT-L29.63Activating More Pixels in Image Super-Resolution Transformer
HAT_FIR29.6SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
HAT29.59Activating More Pixels in Image Super-Resolution Transformer
CPAT+29.59Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
CPAT29.56Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
SwinFIR29.55SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
HAN+29.41Single Image Super-Resolution via a Holistic Attention Network
DRLN+29.4Densely Residual Laplacian Super-Resolution
LTE29.39Local Texture Estimator for Implicit Representation Function
CSNLN29.33Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
SwinOIR29.27Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy
SRFBN29.24Feedback Network for Image Super-Resolution
MWCNN29.12Multi-level Wavelet-CNN for Image Restoration
IMDN29.09Lightweight Image Super-Resolution with Information Multi-distillation Network
RED3028.93Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
LFFN-S28.91Lightweight Feature Fusion Network for Single Image Super-Resolution
LCSCNet28.87LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution
DnCNN-328.85Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
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Image Super Resolution On Bsd100 3X Upscaling | SOTA | HyperAI