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 351–375 of 3874 papers

TitleStatusHype
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-ResolutionCode1
Deep Semantic Statistics Matching (D2SM) Denoising NetworkCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Deep Video Super-Resolution using HR Optical Flow EstimationCode1
DeFMO: Deblurring and Shape Recovery of Fast Moving ObjectsCode1
Deformable 3D Convolution for Video Super-ResolutionCode1
ARM: Any-Time Super-Resolution MethodCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and LatencyCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-ResolutionCode1
Asymmetric CNN for image super-resolutionCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
DeblurSR: Event-Based Motion Deblurring Under the Spiking RepresentationCode1
Adaptive Convolutional Neural Network for Image Super-resolutionCode1
DARTS: Double Attention Reference-based Transformer for Super-resolutionCode1
A Text Attention Network for Spatial Deformation Robust Scene Text Image Super-resolutionCode1
DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution NetworksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified