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 1121–1130 of 3874 papers

TitleStatusHype
BadSR: Stealthy Label Backdoor Attacks on Image Super-Resolution—0
Super-Resolution with Structured Motion—0
Blind Restoration of High-Resolution Ultrasound Video—0
Every Pixel Tells a Story: End-to-End Urdu Newspaper OCR—0
Super-Resolution Optical Coherence Tomography Using Diffusion Model-Based Plug-and-Play Priors—0
Hunyuan-Game: Industrial-grade Intelligent Game Creation Model—0
Enhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?—0
Trustworthy Image Super-Resolution via Generative PseudoinverseCode0
CLIP-aware Domain-Adaptive Super-Resolution—0
Accelerating Diffusion-based Super-Resolution with Dynamic Time-Spatial Sampling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified