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 151–200 of 3874 papers

TitleStatusHype
Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion ModelsCode2
Implicit Diffusion Models for Continuous Super-ResolutionCode2
Learning Generative Structure Prior for Blind Text Image Super-resolutionCode2
SRFormerV2: Taking a Closer Look at Permuted Self-Attention for Image Super-ResolutionCode2
StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned FacesCode2
Spatially-Adaptive Feature Modulation for Efficient Image Super-ResolutionCode2
I^2SB: Image-to-Image Schrödinger BridgeCode2
Image Restoration with Mean-Reverting Stochastic Differential EquationsCode2
Simple diffusion: End-to-end diffusion for high resolution imagesCode2
Reference-based Image and Video Super-Resolution via C2-MatchingCode2
Immersive Neural Graphics PrimitivesCode2
AERO: Audio Super Resolution in the Spectral DomainCode2
Blur Interpolation Transformer for Real-World Motion from BlurCode2
A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact RemovalCode2
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing ImageryCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and RestorationCode2
Text2Light: Zero-Shot Text-Driven HDR Panorama GenerationCode2
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and ResultsCode2
Towards Lightweight Super-Resolution with Dual Regression LearningCode2
Open High-Resolution Satellite Imagery: The WorldStrat Dataset -- With Application to Super-ResolutionCode2
NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling RatesCode2
AnimeSR: Learning Real-World Super-Resolution Models for Animation VideosCode2
VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-ResolutionCode2
Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel FusionCode2
CogView2: Faster and Better Text-to-Image Generation via Hierarchical TransformersCode2
On the Generalization of BasicVSR++ to Video Deblurring and DenoisingCode2
Learning Trajectory-Aware Transformer for Video Super-ResolutionCode2
Reference-based Video Super-Resolution Using Multi-Camera Video TripletsCode2
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-ResolutionCode2
Efficient Long-Range Attention Network for Image Super-resolutionCode2
Pix2NeRF: Unsupervised Conditional π-GAN for Single Image to Neural Radiance Fields TranslationCode2
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Denoising Diffusion Restoration ModelsCode2
Pix2NeRF: Unsupervised Conditional p-GAN for Single Image to Neural Radiance Fields TranslationCode2
Investigating Tradeoffs in Real-World Video Super-ResolutionCode2
CogView: Mastering Text-to-Image Generation via TransformersCode2
Learning Continuous Image Representation with Local Implicit Image FunctionCode2
Fourier Neural Operator for Parametric Partial Differential EquationsCode2
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
Real-World Super-Resolution via Kernel Estimation and Noise InjectionCode2
Lossless Image Compression through Super-ResolutionCode2
A Tour of Convolutional Networks Guided by Linear InterpretersCode2
Recurrent Transition Networks for Character LocomotionCode2
Image Super-Resolution Using Very Deep Residual Channel Attention NetworksCode2
IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-ResolutionCode1
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level VisionCode1
Unsupervised Imaging Inverse Problems with Diffusion Distribution MatchingCode1
DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified