  WiFi human sensing has achieved great progress in indoor localization,
activity classification, etc. Retracing the development of these work, we have
a natural question: can WiFi devices work like cameras for vision applications?
In this paper We try to answer this question by exploring the ability of WiFi
on estimating single person pose. We use a 3-antenna WiFi sender and a
3-antenna receiver to generate WiFi data. Meanwhile, we use a synchronized
camera to capture person videos for corresponding keypoint annotations. We
further propose a fully convolutional network (FCN), termed WiSPPN, to estimate
single person pose from the collected data and annotations. Evaluation on over
80k images (16 sites and 8 persons) replies aforesaid question with a positive
answer. Codes have been made publicly available at
https://github.com/geekfeiw/WiSPPN.
