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 2476–2500 of 3874 papers

TitleStatusHype
Nondestructive thermographic detection of internal defects using pixel-pattern based laser excitation and photothermal super resolution reconstruction—0
Non-invasive hemodynamic analysis for aortic regurgitation using computational fluid dynamics and deep learning—0
UGPNet: Universal Generative Prior for Image Restoration—0
PiPs: a Kernel-based Optimization Scheme for Analyzing Non-Stationary 1D Signals—0
TempNet -- Temporal Super Resolution of Radar Rainfall Products with Residual CNNs—0
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution—0
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes—0
not-so-big-GAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution—0
Novel Super-Resolution Method Based on High Order Nonlocal-Means—0
NSD-DIL: Null-Shot Deblurring Using Deep Identity Learning—0
NSSR-DIL: Null-Shot Image Super-Resolution Using Deep Identity Learning—0
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results—0
CNN-based synthesis of realistic high-resolution LiDAR data—0
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results—0
NTIRE 2021 Challenge on Video Super-Resolution—0
CMISR: Circular Medical Image Super-Resolution—0
NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results—0
CLIP-SR: Collaborative Linguistic and Image Processing for Super-Resolution—0
CLIP-aware Domain-Adaptive Super-Resolution—0
Climate Variable Downscaling with Conditional Normalizing Flows—0
NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results—0
Climate Downscaling: A Deep-Learning Based Super-resolution Model of Precipitation Data with Attention Block and Skip Connections—0
NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified