Autoencoder Models for Point Cloud Environmental Synthesis from WiFi Channel State Information: A Preliminary Study
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
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2025
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| _version_ | 1866916712445640704 |
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| author | Pannone, Daniele Avola, Danilo |
| author_facet | Pannone, Daniele Avola, Danilo |
| contents | This paper introduces a deep learning framework for generating point clouds from WiFi Channel State Information data. We employ a two-stage autoencoder approach: a PointNet autoencoder with convolutional layers for point cloud generation, and a Convolutional Neural Network autoencoder to map CSI data to a matching latent space. By aligning these latent spaces, our method enables accurate environmental point cloud reconstruction from WiFi data. Experimental results validate the effectiveness of our approach, highlighting its potential for wireless sensing and environmental mapping applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_20541 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Autoencoder Models for Point Cloud Environmental Synthesis from WiFi Channel State Information: A Preliminary Study Pannone, Daniele Avola, Danilo Computer Vision and Pattern Recognition Machine Learning This paper introduces a deep learning framework for generating point clouds from WiFi Channel State Information data. We employ a two-stage autoencoder approach: a PointNet autoencoder with convolutional layers for point cloud generation, and a Convolutional Neural Network autoencoder to map CSI data to a matching latent space. By aligning these latent spaces, our method enables accurate environmental point cloud reconstruction from WiFi data. Experimental results validate the effectiveness of our approach, highlighting its potential for wireless sensing and environmental mapping applications. |
| title | Autoencoder Models for Point Cloud Environmental Synthesis from WiFi Channel State Information: A Preliminary Study |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2504.20541 |