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 201250 of 1589 papers

TitleStatusHype
Degradation-Aware Self-Attention Based Transformer for Blind Image Super-ResolutionCode1
Deep Unfolding Network for Image Super-ResolutionCode1
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
Detail-Preserving Transformer for Light Field Image Super-ResolutionCode1
Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-ResolutionCode1
BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical FlowCode1
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality AssessmentCode1
C3-STISR: Scene Text Image Super-resolution with Triple CluesCode1
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution Network with Large InputCode1
CADyQ: Content-Aware Dynamic Quantization for Image Super-ResolutionCode1
Exploiting Raw Images for Real-Scene Super-ResolutionCode1
Exploring Separable Attention for Multi-Contrast MR Image Super-ResolutionCode1
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial NetworkCode1
Adaptive Local Implicit Image Function for Arbitrary-scale Super-resolutionCode1
ESSAformer: Efficient Transformer for Hyperspectral Image Super-resolutionCode1
Deep Burst Super-ResolutionCode1
Aligned Structured Sparsity Learning for Efficient Image Super-ResolutionCode1
Exploring the Low-Pass Filtering Behavior in Image Super-ResolutionCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion ModelsCode1
Deep Adaptive Inference Networks for Single Image Super-ResolutionCode1
Deep Model-Based Super-Resolution with Non-uniform BlurCode1
Does Diffusion Beat GAN in Image Super Resolution?Code1
DREAM: Diffusion Rectification and Estimation-Adaptive ModelsCode1
Equivalent Transformation and Dual Stream Network Construction for Mobile Image Super-ResolutionCode1
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-ResolutionCode1
ARM: Any-Time Super-Resolution MethodCode1
DSR: Towards Drone Image Super-ResolutionCode1
DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-ResolutionCode1
CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-ResolutionCode1
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image DenoisingCode1
Edge-enhanced Feature Distillation Network for Efficient Super-ResolutionCode1
Dual Super-Resolution Learning for Semantic SegmentationCode1
ControlSR: Taming Diffusion Models for Consistent Real-World Image Super ResolutionCode1
Better "CMOS" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-ResolutionCode1
2DQuant: Low-bit Post-Training Quantization for Image Super-ResolutionCode1
Closed-loop Matters: Dual Regression Networks for Single Image Super-ResolutionCode1
A Spectral Diffusion Prior for Hyperspectral Image Super-ResolutionCode1
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance PursuitCode1
Collapsible Linear Blocks for Super-Efficient Super ResolutionCode1
A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-ResolutionCode1
edge-SR: Super-Resolution For The MassesCode1
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
Component Divide-and-Conquer for Real-World Image Super-ResolutionCode1
Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile DevicesCode1
EDPN: Enhanced Deep Pyramid Network for Blurry Image RestorationCode1
CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-ResolutionCode1
Conditional Hyper-Network for Blind Super-Resolution with Multiple DegradationsCode1
Conditional Simulation Using Diffusion Schrödinger BridgesCode1
Frequency Domain-based Perceptual Loss for Super ResolutionCode1
Show:102550
← PrevPage 5 of 32Next →

Benchmark Results

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