1. WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing
- Author
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Huang, Shuokang, Li, Kaihan, You, Di, Chen, Yichong, Lin, Arvin, Liu, Siying, Li, Xiaohui, and McCann, Julie A.
- Subjects
Electrical Engineering and Systems Science - Signal Processing ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Multimedia - Abstract
WiFi-based human sensing has exhibited remarkable potential to analyze user behaviors in a non-intrusive and device-free manner, benefiting applications as diverse as smart homes and healthcare. However, most previous works focus on single-user sensing, which has limited practicability in scenarios involving multiple users. Although recent studies have begun to investigate WiFi-based multi-user sensing, there remains a lack of benchmark datasets to facilitate reproducible and comparable research. To bridge this gap, we present WiMANS, to our knowledge, the first dataset for multi-user sensing based on WiFi. WiMANS contains over 9.4 hours of dual-band WiFi Channel State Information (CSI), as well as synchronized videos, monitoring simultaneous activities of multiple users. We exploit WiMANS to benchmark the performance of state-of-the-art WiFi-based human sensing models and video-based models, posing new challenges and opportunities for future work. We believe WiMANS can push the boundaries of current studies and catalyze the research on WiFi-based multi-user sensing., Comment: We present WiMANS, to our knowledge, the first dataset for multi-user activity sensing based on WiFi
- Published
- 2024