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 3071–3080 of 3874 papers

TitleStatusHype
One Model for Two Tasks: Cooperatively Recognizing and Recovering Low-Resolution Scene Text Images by Iterative Mutual Guidance—0
One-Shot Image Restoration—0
One-Shot Model for Mixed-Precision Quantization—0
One Target, Many Views: Multi-User Fusion for Collaborative Uplink ISAC—0
Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localisation Microscopy with Large Tissue Displacements—0
Online Streaming Video Super-Resolution with Convolutional Look-Up Table—0
Online Video Super-Resolution with Convolutional Kernel Bypass Graft—0
On the modern deep learning approaches for precipitation downscaling—0
On the Robustness of Normalizing Flows for Inverse Problems in Imaging—0
On The Role of Alias and Band-Shift for Sentinel-2 Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified