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 3611–3620 of 3874 papers

TitleStatusHype
Spatio-Temporal Distortion Aware Omnidirectional Video Super-ResolutionCode0
Spatio-Temporal Perception-Distortion Trade-off in Learned Video SRCode0
Improving Super-Resolution Methods via Incremental Residual LearningCode0
MAMNet: Multi-path Adaptive Modulation Network for Image Super-ResolutionCode0
"Zero-Shot" Point Cloud UpsamplingCode0
Improved Pothole Detection Using YOLOv7 and ESRGANCode0
RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-ResolutionCode0
Binary Document Image Super Resolution for Improved Readability and OCR PerformanceCode0
DiffPAD: Denoising Diffusion-based Adversarial Patch DecontaminationCode0
AnyTSR: Any-Scale Thermal Super-Resolution for UAVCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified