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 601–610 of 3874 papers

TitleStatusHype
Towards Geospatial Foundation Models via Continual PretrainingCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Cascaded Temporal Updating Network for Efficient Video Super-ResolutionCode1
Cross-View Hierarchy Network for Stereo Image Super-ResolutionCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-ResolutionCode1
Cascaded Local Implicit Transformer for Arbitrary-Scale Super-ResolutionCode1
3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstructionCode1
3D Human Pose, Shape and Texture from Low-Resolution Images and VideosCode1
CSAKD: Knowledge Distillation with Cross Self-Attention for Hyperspectral and Multispectral Image FusionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified