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 251–300 of 1589 papers

TitleStatusHype
Learning Non-Local Spatial-Angular Correlation for Light Field Image Super-ResolutionCode1
Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function SpaceCode1
Hyperspectral Image Super Resolution with Real Unaligned RGB GuidanceCode1
Hypernetworks build Implicit Neural Representations of SoundsCode1
OSRT: Omnidirectional Image Super-Resolution with Distortion-aware TransformerCode1
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
Deep Random Projector: Accelerated Deep Image PriorCode1
B-Spline Texture Coefficients Estimator for Screen Content Image Super-ResolutionCode1
Boosting Single Image Super-Resolution via Partial Channel ShiftingCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Lightweight Image Super-Resolution with Superpixel Token InteractionCode1
Learning Correction Filter via Degradation-Adaptive Regression for Blind Single Image Super-ResolutionCode1
CutMIB: Boosting Light Field Super-Resolution via Multi-View Image BlendingCode1
Infrared Image Super-Resolution: Systematic Review, and Future TrendsCode1
Meta-Learned Kernel For Blind Super-Resolution Kernel EstimationCode1
U2Net: A General Framework with Spatial-Spectral-Integrated Double U-Net for Image FusionCode1
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-ResolutionCode1
Bridging Component Learning with Degradation Modelling for Blind Image Super-ResolutionCode1
Learning Detail-Structure Alternative Optimization for Blind Super-ResolutionCode1
Global Learnable Attention for Single Image Super-ResolutionCode1
From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-ResolutionCode1
Knowledge Distillation based Degradation Estimation for Blind Super-ResolutionCode1
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image SynthesisCode1
GAN Prior based Null-Space Learning for Consistent Super-ResolutionCode1
Perception-Oriented Single Image Super-Resolution using Optimal Objective EstimationCode1
N-Gram in Swin Transformers for Efficient Lightweight Image Super-ResolutionCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
The Best of Both Worlds: a Framework for Combining Degradation Prediction with High Performance Super-Resolution NetworksCode1
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: ReportCode1
Combining Attention Module and Pixel Shuffle for License Plate Super-ResolutionCode1
Single Image Super-Resolution via a Dual Interactive Implicit Neural NetworkCode1
Efficient Image Super-Resolution using Vast-Receptive-Field AttentionCode1
Single Image Super-Resolution Based on Capsule Neural NetworksCode1
Accurate Image Restoration with Attention Retractable TransformerCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
Multi-scale Attention Network for Single Image Super-ResolutionCode1
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark DatasetCode1
A heterogeneous group CNN for image super-resolutionCode1
Face Super-Resolution Using Stochastic Differential EquationsCode1
KXNet: A Model-Driven Deep Neural Network for Blind Super-ResolutionCode1
Generative Adversarial Super-Resolution at the Edge with Knowledge DistillationCode1
Joint Learning Content and Degradation Aware Feature for Blind Super-ResolutionCode1
DSR: Towards Drone Image Super-ResolutionCode1
Fast Nearest Convolution for Real-Time Efficient Image Super-ResolutionCode1
RZSR: Reference-based Zero-Shot Super-Resolution with Depth Guided Self-ExemplarsCode1
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-ResolutionCode1
AT-DDPM: Restoring Faces degraded by Atmospheric Turbulence using Denoising Diffusion Probabilistic ModelsCode1
Sliding Window Recurrent Network for Efficient Video Super-ResolutionCode1
HST: Hierarchical Swin Transformer for Compressed Image Super-resolutionCode1
Learning Degradation Representations for Image DeblurringCode1
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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