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 251275 of 1589 papers

TitleStatusHype
Multi-Scale Feature Fusion using Channel Transformers for Guided Thermal Image Super Resolution0
LFMamba: Light Field Image Super-Resolution with State Space Model0
A Dictionary Based Approach for Removing Out-of-Focus BlurCode0
Geometric Distortion Guided Transformer for Omnidirectional Image Super-Resolution0
SatDiffMoE: A Mixture of Estimation Method for Satellite Image Super-resolution with Latent Diffusion Models0
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo SimulationCode1
SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-ResolutionCode1
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
One-Step Effective Diffusion Network for Real-World Image Super-ResolutionCode4
Towards Realistic Data Generation for Real-World Super-Resolution0
2DQuant: Low-bit Post-Training Quantization for Image Super-ResolutionCode1
Binarized Diffusion Model for Image Super-ResolutionCode2
Arctic Sea Ice Image Super-Resolution Based on Multi-Scale Convolution and Dual-Gating Mechanism0
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play PriorsCode1
Single image super-resolution based on trainable feature matching attention networkCode0
PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-ResolutionCode1
Does Diffusion Beat GAN in Image Super Resolution?Code1
Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models0
BOLD: Boolean Logic Deep Learning0
Universal Robustness via Median Randomized Smoothing for Real-World Super-Resolution0
Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image GenerationCode2
Perceptual Fairness in Image Restoration0
Infrared Image Super-Resolution via Lightweight Information Split Network0
Frequency-Domain Refinement with Multiscale Diffusion for Super Resolution0
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation ModelCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR29.54Unverified
2HMA†PSNR29.51Unverified
3Hi-IR-LPSNR29.49Unverified
4HAT-LPSNR29.47Unverified
5HAT_FIRPSNR29.44Unverified
6DRCTPSNR29.4Unverified
7HATPSNR29.38Unverified
8CPAT+PSNR29.36Unverified
9SwinFIRPSNR29.36Unverified
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