SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

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Showing 1776–1800 of 3874 papers

TitleStatusHype
Fully Data-Driven Model for Increasing Sampling Rate Frequency of Seismic Data using Super-Resolution Generative Adversarial Networks—0
Spatial-and-Frequency-aware Restoration method for Images based on Diffusion Models—0
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow—0
You Only Need One Step: Fast Super-Resolution with Stable Diffusion via Scale Distillation—0
Vision-Informed Flow Image Super-Resolution with Quaternion Spatial Modeling and Dynamic Flow Convolution—0
Bridging the Domain Gap: A Simple Domain Matching Method for Reference-based Image Super-Resolution in Remote Sensing—0
Reconfigurable AI Modules Aided Channel Estimation and MIMO Detection—0
An efficient dual-branch framework via implicit self-texture enhancement for arbitrary-scale histopathology image super-resolution—0
Face to Cartoon Incremental Super-Resolution using Knowledge Distillation—0
Super Efficient Neural Network for Compression Artifacts Reduction and Super Resolution—0
From Blurry to Brilliant Detection: YOLOv5-Based Aerial Object Detection with Super Resolution—0
When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges—0
Conditional Neural Video Coding with Spatial-Temporal Super-Resolution—0
Combined Generative and Predictive Modeling for Speech Super-resolution—0
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New MethodCode0
Inflation with Diffusion: Efficient Temporal Adaptation for Text-to-Video Super-Resolution—0
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions—0
OFDM Reference Signal Pattern Design Criteria for Integrated Communication and Sensing—0
Efficient Image Super-Resolution via Symmetric Visual Attention Network—0
No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy—0
Sparsity-based background removal for STORM super-resolution imagesCode0
City Scene Super-Resolution via Geometric Error MinimizationCode0
TriNeRFLet: A Wavelet Based Triplane NeRF Representation—0
Frequency-Time Diffusion with Neural Cellular Automata—0
AGG: Amortized Generative 3D Gaussians for Single Image to 3D—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified