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 126–150 of 3874 papers

TitleStatusHype
CFAT: Unleashing Triangular Windows for Image Super-resolutionCode2
Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion ModelsCode2
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
Efficient Attention-Sharing Information Distillation Transformer for Lightweight Single Image Super-ResolutionCode2
Efficient Mixed Transformer for Single Image Super-ResolutionCode2
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-ResolutionCode2
Denoising Diffusion Models for Plug-and-Play Image RestorationCode2
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and ResultsCode2
Denoising Diffusion Restoration ModelsCode2
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive SurveyCode2
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-ResolutionCode2
Distillation-Free One-Step Diffusion for Real-World Image Super-ResolutionCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
DVMSR: Distillated Vision Mamba for Efficient Super-ResolutionCode2
Effective Diffusion Transformer Architecture for Image Super-ResolutionCode2
Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual LossCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel FusionCode2
AERO: Audio Super Resolution in the Spectral DomainCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified