SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 2376–2400 of 3874 papers

TitleStatusHype
Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention—0
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation—0
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN—0
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
LAConv: Local Adaptive Convolution for Image Fusion—0
Self-Conditioned Probabilistic Learning of Video RescalingCode1
Compressed Ultrasound Imaging:from Sub-Nyquist Rates to Super-Resolution—0
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic DataCode4
High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss—0
RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank—0
Joint Implicit Image Function for Guided Depth Super-ResolutionCode1
ProfileSR-GAN: A GAN based Super-Resolution Method for Generating High-Resolution Load Profiles—0
Joint Semi-supervised 3D Super-Resolution and Segmentation with Mixed Adversarial Gaussian Domain Adaptation—0
Level generation and style enhancement -- deep learning for game development overview—0
Multi-Attention Generative Adversarial Network for Remote Sensing Image Super-Resolution—0
Single-shot structured illumination microscopy—0
Real-Time Super-Resolution System of 4K-Video Based on Deep LearningCode1
Learned super resolution ultrasound for improved breast lesion characterization—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
Image restoration quality assessment based on regional differential information entropy—0
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation—0
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving—0
Blind Image Super-Resolution: A Survey and Beyond—0
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows—0
A Deep Residual Star Generative Adversarial Network for multi-domain Image Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified