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 1–25 of 1589 papers

TitleStatusHype
SpectraLift: Physics-Guided Spectral-Inversion Network for Self-Supervised Hyperspectral Image Super-Resolution—0
IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-ResolutionCode1
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
Structural Similarity-Inspired Unfolding for Lightweight Image Super-ResolutionCode1
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
Practical Manipulation Model for Robust Deepfake DetectionCode0
Multi-scale Image Super Resolution with a Single Auto-Regressive Model—0
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-ResolutionCode0
Text-Aware Real-World Image Super-Resolution via Diffusion Model with Joint Segmentation DecodersCode0
Enhancing Frequency for Single Image Super-Resolution with Learnable Separable Kernels—0
A Tree-guided CNN for image super-resolutionCode1
Application of convolutional neural networks in image super-resolution—0
Beyond Pretty Pictures: Combined Single- and Multi-Image Super-resolution for Sentinel-2 Images—0
Advancing Image Super-resolution Techniques in Remote Sensing: A Comprehensive Survey—0
TextSR: Diffusion Super-Resolution with Multilingual OCR Guidance—0
SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language ModelCode0
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
Burst Image Super-Resolution via Multi-Cross Attention Encoding and Multi-Scan State-Space Decoding—0
Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment—0
BadSR: Stealthy Label Backdoor Attacks on Image Super-Resolution—0
Every Pixel Tells a Story: End-to-End Urdu Newspaper OCR—0
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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