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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1461–1470 of 3874 papers

TitleStatusHype
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models—0
Tunable Convolutions with Parametric Multi-Loss OptimizationCode1
CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images—0
Burstormer: Burst Image Restoration and Enhancement TransformerCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation TransformerCode1
Image-to-image domain adaptation for vehicle re-identification—0
Dual Circle Contrastive Learning-Based Blind Image Super-Resolution—0
Implicit Diffusion Models for Continuous Super-ResolutionCode2
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified