# Person-in-WiFi: Fine-grained Person Perception using WiFi

arXiv: https://arxiv.org/abs/1904.00276 · HTML: https://mlsanity.com/paper/1904.00276/

## Key facts

- Cited by 57 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Mar 2019.

## Built on by (most cited first, 30 of 57)

- [SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing](https://mlsanity.com/paper/2207.07859/) (2022)
- [mmBody Benchmark: 3D Body Reconstruction Dataset and Analysis for Millimeter Wave Radar](https://mlsanity.com/paper/2209.05070/) (2022)
- [HuPR: A Benchmark for Human Pose Estimation Using Millimeter Wave Radar](https://mlsanity.com/paper/2210.12564/) (2022)
- [2D Human Pose Estimation: A Survey](https://mlsanity.com/paper/2204.07370/) (2022)
- [Towards Domain-Independent and Real-Time Gesture Recognition Using mmWave Signal](https://mlsanity.com/paper/2111.06195/) (2021)
- [WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing](https://mlsanity.com/paper/2402.09430/) (2024)
- [Unsupervised Learning for Human Sensing Using Radio Signals](https://mlsanity.com/paper/2207.02370/) (2022)
- [DensePose From WiFi](https://mlsanity.com/paper/2301.00250/) (2022)
- [AdaPose: Towards Cross-Site Device-Free Human Pose Estimation with Commodity WiFi](https://mlsanity.com/paper/2309.16964/) (2023)
- [RFBoost: Understanding and Boosting Deep WiFi Sensing via Physical Data Augmentation](https://mlsanity.com/paper/2410.07230/) (2024)
- [XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses](https://mlsanity.com/paper/2501.19034/) (2025)
- [A Survey on Wi-Fi Sensing Generalizability: Taxonomy, Techniques, Datasets, and Future Research Prospects](https://mlsanity.com/paper/2503.08008/) (2025)
- [AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communications](https://mlsanity.com/paper/2205.09115/) (2022)
- [Towards Robust and Realistic Human Pose Estimation via WiFi Signals](https://mlsanity.com/paper/2501.09411/) (2025)
- [WiCluster: Passive Indoor 2D/3D Positioning using WiFi without Precise Labels](https://mlsanity.com/paper/2107.01002/) (2021)
- [RFGAN: RF-Based Human Synthesis](https://mlsanity.com/paper/2112.03727/) (2021)
- [Forgery Attack Detection in Surveillance Video Streams Using Wi-Fi Channel State Information](https://mlsanity.com/paper/2201.09487/) (2022)
- [Quantum Transfer Learning for Wi-Fi Sensing](https://mlsanity.com/paper/2205.08590/) (2022)
- [You Can Wash Hands Better: Accurate Daily Handwashing Assessment with a Smartwatch](https://mlsanity.com/paper/2112.06657/) (2021)
- [Human Silhouette and Skeleton Video Synthesis through Wi-Fi signals](https://mlsanity.com/paper/2203.05864/) (2022)
- [3D Human Pose Estimation for Free-from and Moving Activities Using WiFi](https://mlsanity.com/paper/2204.07878/) (2022)
- [WiFi-JEPA: Self-supervised Learning for WiFi-CSI 3D Human Pose Estimation](https://mlsanity.com/paper/2607.11064/) (2026)
- [Multi-Band Wi-Fi Sensing with Matched Feature Granularity](https://mlsanity.com/paper/2112.14006/) (2021)
- [3D Human Mesh Construction Leveraging Wi-Fi](https://mlsanity.com/paper/2210.10957/) (2022)
- [RFPose-OT: RF-Based 3D Human Pose Estimation via Optimal Transport Theory](https://mlsanity.com/paper/2301.13013/) (2022)
- [OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision](https://mlsanity.com/paper/2308.10146/) (2023)
- [MAC: ModAlity Calibration for Object Detection](https://mlsanity.com/paper/2310.09461/) (2023)
- [Non-contact Multimodal Indoor Human Monitoring Systems: A Survey](https://mlsanity.com/paper/2312.07601/) (2023)
- [Radio Frequency Signal based Human Silhouette Segmentation: A Sequential Diffusion Approach](https://mlsanity.com/paper/2407.19244/) (2024)
- [mmEgoHand: Egocentric Hand Pose Estimation and Gesture Recognition with Head-mounted Millimeter-wave Radar and IMU](https://mlsanity.com/paper/2501.13805/) (2025)

## Abstract (arXiv)

Fine-grained person perception such as body segmentation and pose estimation has been achieved with many 2D and 3D sensors such as RGB/depth cameras, radars (e.g., RF-Pose) and LiDARs. These sensors capture 2D pixels or 3D point clouds of person bodies with high spatial resolution, such that the existing Convolutional Neural Networks can be directly applied for perception. In this paper, we take one step forward to show that fine-grained person perception is possible even with 1D sensors: WiFi antennas. To our knowledge, this is the first work to perceive persons with pervasive WiFi devices, which is cheaper and power efficient than radars and LiDARs, invariant to illumination, and has little privacy concern comparing to cameras. We used two sets of off-the-shelf WiFi antennas to acquire signals, i.e., one transmitter set and one receiver set. Each set contains three antennas lined-up as a regular household WiFi router. The WiFi signal generated by a transmitter antenna, penetrates through and reflects on human bodies, furniture and walls, and then superposes at a receiver antenna as a 1D signal sample (instead of 2D pixels or 3D point clouds). We developed a deep learning approach that uses annotations on 2D images, takes the received 1D WiFi signals as inputs, and performs body segmentation and pose estimation in an end-to-end manner. Experimental results on over 100000 frames under 16 indoor scenes demonstrate that Person-in-WiFi achieved person perception comparable to approaches using 2D images.