Open Access
2- https://doi.org/10.1109/icip51287.2024.10647775
Through-Wall Imaging Based On WiFi Channel State Information
This study introduces a method to generate images from WiFi Channel State Information in through-wall scenarios using a multimodal Variational Autoencoder, enabling visual monitoring and activity recognition without cameras; evaluations show the approach is viable and promising for practical use.
Translate Article 
This work presents a seminal approach for synthesizing images from WiFi Channel State Information (CSI) in throughwall scenarios. Leveraging the strengths of WiFi, such as cost-effectiveness, illumination invariance, and wallpenetrating capabilities, our approach enables visual monitoring of indoor environments beyond room boundaries and without the need for cameras. More generally, it improves the interpretability of WiFi CSI by unlocking the option to perform image-based downstream tasks, e.g., visual activity recognition. In order to achieve this crossmodal translation from WiFi CSI to images, we rely on a multimodal Variational Autoencoder (VAE) adapted to our problem specifics. We extensively evaluate our proposed methodology through an ablation study on architecture configuration and a quantitative/qualitative assessment of reconstructed images. Our results demonstrate the viability of our method and highlight its potential for practical applications.
