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 3011–3020 of 3874 papers

TitleStatusHype
Seeing Eye to AI? Applying Deep-Feature-Based Similarity Metrics to Information Visualization—0
Architecture-aware Network Pruning for Vision Quality Applications—0
Arbitrary Scale Super-Resolution Assisted Lunar Crater Detection in Satellite Images—0
AccDecoder: Accelerated Decoding for Neural-enhanced Video Analytics—0
Super Images -- A New 2D Perspective on 3D Medical Imaging Analysis—0
A Boosting Method to Face Image Super-resolution—0
SEGSRNet for Stereo-Endoscopic Image Super-Resolution and Surgical Instrument Segmentation—0
Seirios: Leveraging Multiple Channels for LoRaWAN Indoor and Outdoor Localization—0
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals—0
Arbitrary-Scale Image Generation and Upsampling using Latent Diffusion Model and Implicit Neural Decoder—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified