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| Main Authors: | , , , , , |
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| Format: | Recurso digital |
| Language: | |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17830310 |
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Table of Contents:
- <p>Test split from the dataset presented in the paper "A Holistic Comparison of Performance and Efficiency between Von Neumann and Neuromorphic Computing in a Real-World Application"</p> <p>This split is part of an aerial beach dataset that captured the dynamic activity of surfers, swimmers, and beach users from drone-mounted vision sensors. It offers synchronized data obtained through conventional frame-based and event-based cameras for multi-modal analysis of real-world coastal environments. </p> <p><strong>Dataset structure</strong></p> <ul> <li> <p>The split is organized into <strong>four top-level folders</strong>, one per beach.</p> </li> <li> <p>Inside each beach folder there are <strong>three modality subfolders</strong>:</p> <ul> <li> <p><code>classic/</code> — frame images in <strong>PNG</strong> format</p> </li> <li> <p><code>events/</code> — event-based images in <strong>PNG</strong> format</p> </li> <li> <p><code>tensors/</code> — event-based tensors in <strong>PyTorch <code>.pt</code></strong> format</p> </li> </ul> </li> </ul> <p><strong>Annotations</strong></p> <ul> <li> <p>Each modality folder contains a <code>labels_detection/</code> subfolder.</p> </li> <li> <p>Within <code>labels_detection/</code>, <strong>ZIP files</strong> are provided; <strong>each ZIP</strong> contains an <code>annotations.xml</code> file (CVAT format) with the <strong>bounding boxes and class labels</strong> corresponding to its paired data file (<code>.png</code> or <code>.pt</code>).</p> </li> </ul>