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

Showing 101–125 of 1589 papers

TitleStatusHype
Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-ResolutionCode2
Efficient Long-Range Attention Network for Image Super-resolutionCode2
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution PriorsCode2
Deep Constrained Least Squares for Blind Image Super-ResolutionCode2
Learning Continuous Image Representation with Local Implicit Image FunctionCode2
AIM 2020 Challenge on Efficient Super-Resolution: Methods and ResultsCode2
Real-World Super-Resolution via Kernel Estimation and Noise InjectionCode2
Image Super-Resolution Using Very Deep Residual Channel Attention NetworksCode2
IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-ResolutionCode1
Structural Similarity-Inspired Unfolding for Lightweight Image Super-ResolutionCode1
A Tree-guided CNN for image super-resolutionCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
Semantic-Guided Diffusion Model for Single-Step Image Super-ResolutionCode1
Small Clips, Big Gains: Learning Long-Range Refocused Temporal Information for Video Super-ResolutionCode1
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and ResultsCode1
TTRD3: Texture Transfer Residual Denoising Dual Diffusion Model for Remote Sensing Image Super-ResolutionCode1
Enhanced Semantic Extraction and Guidance for UGC Image Super ResolutionCode1
PIDSR: Complementary Polarized Image Demosaicing and Super-ResolutionCode1
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality AssessmentCode1
QDM: Quadtree-Based Region-Adaptive Sparse Diffusion Models for Efficient Image Super-ResolutionCode1
MegaSR: Mining Customized Semantics and Expressive Guidance for Image Super-ResolutionCode1
QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-ResolutionCode1
CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-ResolutionCode1
Heterogeneous Mixture of Experts for Remote Sensing Image Super-ResolutionCode1
HSRMamba: Contextual Spatial-Spectral State Space Model for Single Image Hyperspectral Super-ResolutionCode1
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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
6DRCTPSNR28.06—Unverified
7CPAT+PSNR28.06—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