Improve dataset card: Add robotics task category, abstract, and enhance formatting

README.md

@@ -1,11 +1,19 @@
-# LoFi
+---
+task_categories:
+- robotics
+---
 
-The description is generated by Grok3.
+# LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking
+
+Paper: [LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking](https://arxiv.org/abs/2412.05074)
+Code: [https://github.com/RS2002/LoFi](https://github.com/RS2002/LoFi)
+
+## Abstract
+
+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 .
 
 ## Dataset Description
 
-- **Repository:** [RS2002/LoFi: Official Repository for The Paper, LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracing](https://github.com/RS2002/LoFi)
-- **Paper:** [LoFi: Vision-Aided Label Generator for Wi-Fi Localization and Tracking](https://arxiv.org/abs/2412.05074), IEEE Globecom GenAI NGN Workshop 2025
 - **Contact:** [zzhaock@connect.ust.hk](mailto:zzhaock@connect.ust.hk)  
 - **Collectors:** Zijian Zhao, Tingwei Chen  
 - **Organization:** AI-RAN Lab (hosted by Prof. Guangxu Zhu) in SRIBD, CUHK(SZ)