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 1751–1775 of 3874 papers

TitleStatusHype
Image Enhancement by Recurrently-trained Super-resolution Network—0
Benchmarking Super-Resolution Algorithms on Real Data—0
Image inpainting for corrupted images by using the semi-super resolution GAN—0
Image Inpainting for High-Resolution Textures using CNN Texture Synthesis—0
Image Neural Field Diffusion Models—0
Imagen Video: High Definition Video Generation with Diffusion Models—0
ImagePairs: Realistic Super Resolution Dataset via Beam Splitter Camera Rig—0
Image Processing GNN: Breaking Rigidity in Super-Resolution—0
Fast single image super-resolution based on sigmoid transformation—0
Convolutional neural network based on sparse graph attention mechanism for MRI super-resolution—0
Fast Single Image Super-Resolution—0
Convolutional Low-Resolution Fine-Grained Classification—0
Deep machine learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging—0
Image Resolution Enhancement by Using Interpolation Followed by Iterative Back Projection—0
Image Restoration by Deep Projected GSURE—0
A Single-Frame and Multi-Frame Cascaded Image Super-Resolution Method—0
Fast Randomized-MUSIC for mm-Wave Massive MIMO Radars—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Convolutional Bipartite Attractor Networks—0
Image Restoration using Autoencoding Priors—0
A Comprehensive Survey of Transformers for Computer Vision—0
Deep MR Image Super-Resolution Using Structural Priors—0
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter—0
A Simple Plugin for Transforming Images to Arbitrary Scales—0
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified