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.

RTSR: A Real-Time Super-Resolution Model for AV1 Compressed Content

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Nov 20, 2024
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HF-Diff: High-Frequency Perceptual Loss and Distribution Matching for One-Step Diffusion-Based Image Super-Resolution

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Nov 20, 2024
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Adversarial Diffusion Compression for Real-World Image Super-Resolution

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Nov 20, 2024
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ISAC Super-Resolution Receivers: The Effect of Different Dictionary Matrices

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Nov 19, 2024
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Contourlet Refinement Gate Framework for Thermal Spectrum Distribution Regularized Infrared Image Super-Resolution

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Nov 19, 2024
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Efficient Medicinal Image Transmission and Resolution Enhancement via GAN

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Nov 19, 2024
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Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution

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Nov 18, 2024
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A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift

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Nov 15, 2024
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DiffFNO: Diffusion Fourier Neural Operator

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Nov 15, 2024
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Performance Boundaries and Tradeoffs in Super-Resolution Imaging Technologies for Space Targets

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Nov 14, 2024
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