SOTAVerified

Image Super-Resolution

Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.

Papers

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Showing 501–550 of 1589 papers

TitleStatusHype
Closed-loop Matters: Dual Regression Networks for Single Image Super-ResolutionCode1
Stochastic Frequency Masking to Improve Super-Resolution and Denoising NetworksCode1
Hierarchical Neural Architecture Search for Single Image Super-ResolutionCode1
Creating High Resolution Images with a Latent Adversarial GeneratorCode1
Gated Fusion Network for Degraded Image Super ResolutionCode1
Meta-Transfer Learning for Zero-Shot Super-ResolutionCode1
Unpaired Image Super-Resolution using Pseudo-SupervisionCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial NetworkCode1
Convolutional Neural Networks with Intermediate Loss for 3D Super-Resolution of CT and MRI ScansCode1
HighRes-net: Multi-Frame Super-Resolution by Recursive FusionCode1
Scale-wise Convolution for Image RestorationCode1
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
Spatial-Angular Interaction for Light Field Image Super-ResolutionCode1
Lightweight Image Super-Resolution with Information Multi-distillation NetworkCode1
Underwater Image Super-Resolution using Deep Residual MultipliersCode1
Learning Filter Basis for Convolutional Neural Network CompressionCode1
Learned Image Downscaling for Upscaling using Content Adaptive ResamplerCode1
Single Image Super-Resolution via CNN Architectures and TV-TV MinimizationCode1
Generative Adversarial Networks in Computer Vision: A Survey and TaxonomyCode1
Towards Real Scene Super-Resolution with Raw ImagesCode1
SinGAN: Learning a Generative Model from a Single Natural ImageCode1
Deep Plug-and-Play Super-Resolution for Arbitrary Blur KernelsCode1
Meta-SR: A Magnification-Arbitrary Network for Super-ResolutionCode1
How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale ApproachCode1
Learning Temporal Coherence via Self-Supervision for GAN-based Video GenerationCode1
Blockwise Parallel Decoding for Deep Autoregressive ModelsCode1
The 2018 PIRM Challenge on Perceptual Image Super-resolutionCode1
The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolutionCode1
An efficient CNN for spectral reconstruction from RGB imagesCode1
Enhanced Deep Residual Networks for Single Image Super-ResolutionCode1
Face Super-Resolution Through Wasserstein GANsCode1
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural NetworkCode1
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial NetworkCode1
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image DenoisingCode1
Accelerating the Super-Resolution Convolutional Neural NetworkCode1
Perceptual Losses for Real-Time Style Transfer and Super-ResolutionCode1
Image Super-Resolution Using Deep Convolutional NetworksCode1
SpectraLift: Physics-Guided Spectral-Inversion Network for Self-Supervised Hyperspectral Image Super-Resolution—0
Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution—0
Unsupervised Image Super-Resolution Reconstruction Based on Real-World Degradation Patterns—0
Efficient Star Distillation Attention Network for Lightweight Image Super-Resolution—0
Stroke-based Cyclic Amplifier: Image Super-Resolution at Arbitrary Ultra-Large Scales—0
Incorporating Uncertainty-Guided and Top-k Codebook Matching for Real-World Blind Image Super-Resolution—0
Task-driven real-world super-resolution of document scans—0
Text-Aware Real-World Image Super-Resolution via Diffusion Model with Joint Segmentation DecodersCode0
Multi-scale Image Super Resolution with a Single Auto-Regressive Model—0
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-ResolutionCode0
Practical Manipulation Model for Robust Deepfake DetectionCode0
Enhancing Frequency for Single Image Super-Resolution with Learnable Separable Kernels—0
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All datasetsSet14 - 4x upscalingBSD100 - 4x upscalingUrban100 - 4x upscalingManga109 - 4x upscalingSet5 - 2x upscalingSet14 - 2x upscalingSet5 - 3x upscalingBSD100 - 2x upscalingUrban100 - 2x upscalingSet14 - 3x upscalingUrban100 - 3x upscalingBSD100 - 3x upscaling

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR29.54—Unverified
2HMA†PSNR29.51—Unverified
3Hi-IR-LPSNR29.49—Unverified
4HAT-LPSNR29.47—Unverified
5HAT_FIRPSNR29.44—Unverified
6DRCTPSNR29.4—Unverified
7HATPSNR29.38—Unverified
8CPAT+PSNR29.36—Unverified
9SwinFIRPSNR29.36—Unverified
10CPATPSNR29.34—Unverified
#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR28.16—Unverified
2HMA†PSNR28.13—Unverified
3Hi-IR-LPSNR28.13—Unverified
4HAT-LPSNR28.09—Unverified
5HAT_FIRPSNR28.07—Unverified
6CPAT+PSNR28.06—Unverified
7DRCTPSNR28.06—Unverified
8HATPSNR28.05—Unverified
9CPATPSNR28.04—Unverified
10SwinFIRPSNR28.03—Unverified
#ModelMetricClaimedVerifiedStatus
1Hi-IR-LPSNR28.72—Unverified
2DRCT-LPSNR28.7—Unverified
3HMA†PSNR28.69—Unverified
4HAT-LPSNR28.6—Unverified
5HAT_FIRPSNR28.43—Unverified
6DRCTPSNR28.4—Unverified
7HATPSNR28.37—Unverified
8CPAT+PSNR28.33—Unverified
9CPATPSNR28.22—Unverified
10PFTPSNR28.2—Unverified