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 361–370 of 3874 papers

TitleStatusHype
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-ResolutionCode1
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-ResolutionCode1
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution NetworksCode1
Cylin-Painting: Seamless 360 Panoramic Image Outpainting and BeyondCode1
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change ProjectionsCode1
D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-ResolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified