Improve dataset card: Add robotics task category, abstract, and enhance formatting (#1)
Browse files- Improve dataset card: Add robotics task category, abstract, and enhance formatting (d051f0175177cb5353207960989f4b626ae6d746)
Co-authored-by: Niels Rogge <[email protected]>
README.md
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## Dataset Description
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- **Repository:** [RS2002/LoFi: Official Repository for The Paper, LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracing](https://github.com/RS2002/LoFi)
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- **Paper:** [LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking](https://arxiv.org/abs/2412.05074), IEEE Globecom GenAI NGN Workshop 2025
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- **Contact:** [[email protected]](mailto:[email protected])
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- **Collectors:** Zijian Zhao, Tingwei Chen
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- **Organization:** AI-RAN Lab (hosted by Prof. Guangxu Zhu) in SRIBD, CUHK(SZ)
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task_categories:
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- robotics
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# LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking
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Paper: [LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking](https://arxiv.org/abs/2412.05074)
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Code: [https://github.com/RS2002/LoFi](https://github.com/RS2002/LoFi)
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## Abstract
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Data-driven Wi-Fi localization and tracking have shown great promise due to their lower reliance on specialized hardware compared to model-based methods. However, most existing data collection techniques provide only coarse-grained ground truth or a limited number of labeled points, significantly hindering the advancement of data-driven approaches. While systems like lidar can deliver precise ground truth, their high costs make them inaccessible to many users. To address these challenges, we propose LoFi, a vision-aided label generator for Wi-Fi localization and tracking. LoFi can generate ground truth position coordinates solely from 2D images, offering high precision, low cost, and ease of use. Utilizing our method, we have compiled a Wi-Fi tracking and localization dataset using the ESP32-S3 and a webcam. The code and dataset of this paper are available at this https URL .
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## Dataset Description
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- **Contact:** [[email protected]](mailto:[email protected])
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- **Collectors:** Zijian Zhao, Tingwei Chen
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- **Organization:** AI-RAN Lab (hosted by Prof. Guangxu Zhu) in SRIBD, CUHK(SZ)
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