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홈플랫폼문서뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Image Super Resolution On Bsd100 4X Upscaling

평가 지표

PSNR
SSIM

평가 결과

이 벤치마크에서 각 모델의 성능 결과

Paper TitleRepository
DRCT-L28.160.7577DRCT: Saving Image Super-resolution away from Information Bottleneck
Hi-IR-L28.130.7622Hierarchical Information Flow for Generalized Efficient Image Restoration-
HMA†28.130.7562HMANet: Hybrid Multi-Axis Aggregation Network for Image Super-Resolution
HAT-L28.090.7551Activating More Pixels in Image Super-Resolution Transformer
HAT_FIR28.07-SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
DRCT28.060.7533DRCT: Saving Image Super-resolution away from Information Bottleneck
CPAT+28.060.7532Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
HAT28.050.7534Activating More Pixels in Image Super-Resolution Transformer
CPAT28.040.7527Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution-
SwinFIR28.030.7520SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
WaveMixSR-V227.870.764WaveMixSR-V2: Enhancing Super-resolution with Higher Efficiency
DRLN+27.870.7453Densely Residual Laplacian Super-Resolution
LTE27.86-Local Texture Estimator for Implicit Representation Function
SAN27.860.7457Second-Order Attention Network for Single Image Super-Resolution-
HAN+27.850.7454Single Image Super-Resolution via a Holistic Attention Network
SRGAN + Residual-in-Residual Dense Block27.850.7455ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
RFN27.83-Progressive Perception-Oriented Network for Single Image Super-Resolution
ABPN27.820.743Image Super-Resolution via Attention based Back Projection Networks
CSNLN27.80.7439Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
ProSR27.79-A Fully Progressive Approach to Single-Image Super-Resolution
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