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.

Decoupling Multi-Contrast Super-Resolution: Pairing Unpaired Synthesis with Implicit Representations

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May 09, 2025
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EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution

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May 08, 2025
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Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt

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May 08, 2025
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StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation

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May 07, 2025
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EvEnhancer: Empowering Effectiveness, Efficiency and Generalizability for Continuous Space-Time Video Super-Resolution with Events

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May 07, 2025
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A Fusion-Guided Inception Network for Hyperspectral Image Super-Resolution

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May 06, 2025
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Deep Learning Framework for Infrastructure Maintenance: Crack Detection and High-Resolution Imaging of Infrastructure Surfaces

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May 06, 2025
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Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks

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May 06, 2025
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USF Spectral Estimation: Prevalence of Gaussian Cramér-Rao Bounds Despite Modulo Folding

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May 06, 2025
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Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution

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May 05, 2025
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