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 3211–3220 of 3874 papers

TitleStatusHype
Rapid Whole-Heart CMR with Single Volume Super-resolution—0
Rate-Distortion Optimized Post-Training Quantization for Learned Image Compression—0
aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio—0
RBPGAN: Recurrent Back-Projection GAN for Video Super Resolution—0
RDRN: Recursively Defined Residual Network for Image Super-Resolution—0
Real-GDSR: Real-World Guided DSM Super-Resolution via Edge-Enhancing Residual Network—0
Real Image Super-Resolution using GAN through modeling of LR and HR process—0
Real Image Super Resolution Via Heterogeneous Model Ensemble using GP-NAS—0
Realistic Hair Synthesis with Generative Adversarial Networks—0
Real-time, low-cost multi-person 3D pose estimation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified