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 2971–2980 of 3874 papers

TitleStatusHype
Video compression with low complexity CNN-based spatial resolution adaptation—0
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements—0
Video-Specific Autoencoders for Exploring, Editing and Transmitting Videos—0
Video Face Super-Resolution with Motion-Adaptive Feedback Cell—0
VideoGigaGAN: Towards Detail-rich Video Super-Resolution—0
Video Interpolation with Diffusion Models—0
Video Restoration with a Deep Plug-and-Play Prior—0
Rethinking Video Super-Resolution: Towards Diffusion-Based Methods without Motion Alignment—0
Video Super Resolution Based on Deep Learning: A Comprehensive Survey—0
Video super-resolution for single-photon LIDAR—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified