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 2041–2050 of 3874 papers

TitleStatusHype
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference ModelingCode1
Super-Resolution for Selfie Biometrics: Introduction and Application to Face and Iris—0
On the Generalization of BasicVSR++ to Video Deblurring and DenoisingCode2
Denoiser-based projections for 2-D super-resolution multi-reference alignmentCode0
Dual-Stage Approach Toward Hyperspectral Image Super-ResolutionCode1
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning—0
HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area SurveillanceCode0
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-ResolutionCode1
Learning Trajectory-Aware Transformer for Video Super-ResolutionCode2
Evaluating the Adversarial Robustness for Fourier Neural Operators—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified