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 3731–3740 of 3874 papers

TitleStatusHype
FuseSR: Super Resolution for Real-time Rendering through Efficient Multi-resolution Fusion—0
Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution—0
Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images—0
TextSR: Diffusion Super-Resolution with Multilingual OCR Guidance—0
GameIR: A Large-Scale Synthesized Ground-Truth Dataset for Image Restoration over Gaming Content—0
Wavelet-SRNet: A Wavelet-Based CNN for Multi-Scale Face Super Resolution—0
GAN-Based Architecture for Low-dose Computed Tomography Imaging Denoising—0
GAN-based Projector for Faster Recovery with Convergence Guarantees in Linear Inverse Problems—0
GAN-based Super-Resolution and Segmentation of Retinal Layers in Optical coherence tomography Scans—0
Effectiveness of State-of-the-Art Super Resolution Algorithms in Surveillance Environment—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified