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 3126–3150 of 3874 papers

TitleStatusHype
Single Image Super-Resolution via Cascaded Multi-Scale Cross Network—0
Angle of Arrival Estimation with Transformer: A Sparse and Gridless Method with Zero-Shot Capability—0
Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis—0
Single Image Super Resolution via Manifold Approximation—0
Single Image Super-Resolution via Residual Neuron Attention Networks—0
Single Image Super Resolution - When Model Adaptation Matters—0
Single Image Super-resolution with a Switch Guided Hybrid Network for Satellite Images—0
VESR-Net: The Winning Solution to Youku Video Enhancement and Super-Resolution Challenge—0
Single-Layer Learnable Activation for Implicit Neural Representation (SL^2A-INR)—0
A New Super-Resolution Measurement of Perceptual Quality and Fidelity—0
Single MR Image Super-Resolution via Channel Splitting and Serial Fusion Network—0
Single particle algorithms to reveal cellular nanodomain organization—0
Single-photon Image Super-resolution via Self-supervised Learning—0
Single-pixel imaging based on deep learning—0
Single-sample image-fusion upsampling of fluorescence lifetime images—0
Single-shot structured illumination microscopy—0
Single-snapshot machine learning for super-resolution of turbulence—0
Single Snapshot Super-Resolution DOA Estimation for Arbitrary Array Geometries—0
Single-Step Latent Consistency Model for Remote Sensing Image Super-Resolution—0
A New Real-World Video Dataset for the Comparison of Defogging Algorithms—0
Sinogram super-resolution and denoising convolutional neural network (SRCN) for limited data photoacoustic tomography—0
VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution—0
High-resolution Multi-spectral Image Guided DEM Super-resolution using Sinkhorn Regularized Adversarial Network—0
SIR-DIFF: Sparse Image Sets Restoration with Multi-View Diffusion Model—0
A New Approach for Super resolution by Using Web Images and FFT Based Image Registration—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified