# GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning

arXiv: https://arxiv.org/abs/2208.14326 · HTML: https://mlsanity.com/paper/2208.14326/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 75 references that are in the map.
- First posted on arXiv 30 Aug 2022.

## Builds on (most cited first, 14 of 14)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [In Defense of the Triplet Loss for Person Re-Identification](https://mlsanity.com/paper/1703.07737/) (2017)
- [Deep Face Recognition: A Survey](https://mlsanity.com/paper/1804.06655/) (2018)
- [GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition](https://mlsanity.com/paper/1811.06186/) (2018)
- [Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation](https://mlsanity.com/paper/2011.01461/) (2020)
- [Improving Person Re-identification by Attribute and Identity Learning](https://mlsanity.com/paper/1703.07220/) (2017)
- [Autoregressive Moving Average Graph Filtering](https://mlsanity.com/paper/1602.04436/) (2016)
- [Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions](https://mlsanity.com/paper/2107.13782/) (2021)
- [EfficientFi: Towards Large-Scale Lightweight WiFi Sensing via CSI Compression](https://mlsanity.com/paper/2204.04138/) (2022)
- [MetaFi: Device-Free Pose Estimation via Commodity WiFi for Metaverse Avatar Simulation](https://mlsanity.com/paper/2208.10414/) (2022)
- [Attention-based Dual-stream Vision Transformer for Radar Gait Recognition](https://mlsanity.com/paper/2111.12290/) (2021)
- [Trait of Gait: A Survey on Gait Biometrics](https://mlsanity.com/paper/1903.10744/) (2019)

## Built on by (most cited first, 12 of 12)

- [AirFi: Empowering WiFi-based Passive Human Gesture Recognition to Unseen Environment via Domain Generalization](https://mlsanity.com/paper/2209.10285/) (2022)
- [AdaPose: Towards Cross-Site Device-Free Human Pose Estimation with Commodity WiFi](https://mlsanity.com/paper/2309.16964/) (2023)
- [Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing](https://mlsanity.com/paper/2410.01825/) (2024)
- [MaskFi: Unsupervised Learning of WiFi and Vision Representations for Multimodal Human Activity Recognition](https://mlsanity.com/paper/2402.19258/) (2024)
- [Self-Supervised Learning for WiFi CSI-Based Human Activity Recognition: A Systematic Study](https://mlsanity.com/paper/2308.02412/) (2023)
- [Non-contact Multimodal Indoor Human Monitoring Systems: A Survey](https://mlsanity.com/paper/2312.07601/) (2023)
- [CSI4Free: GAN-Augmented mmWave CSI for Improved Pose Classification](https://mlsanity.com/paper/2406.18684/) (2024)
- [ViFi-ReID: A Two-Stream Vision-WiFi Multimodal Approach for Person Re-identification](https://mlsanity.com/paper/2410.09875/) (2024)
- [NVP-HRI: Zero Shot Natural Voice and Posture-based Human-Robot Interaction via Large Language Model](https://mlsanity.com/paper/2503.09335/) (2025)
- [ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements](https://mlsanity.com/paper/2310.03140/) (2023)
- [TRGR: Transmissive RIS-aided Gait Recognition Through Walls](https://mlsanity.com/paper/2407.21566/) (2024)
- [FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing](https://mlsanity.com/paper/2512.22143/) (2025)

## Abstract (arXiv)

As an important biomarker for human identification, human gait can be collected at a distance by passive sensors without subject cooperation, which plays an essential role in crime prevention, security detection and other human identification applications. At present, most research works are based on cameras and computer vision techniques to perform gait recognition. However, vision-based methods are not reliable when confronting poor illuminations, leading to degrading performances. In this paper, we propose a novel multimodal gait recognition method, namely GaitFi, which leverages WiFi signals and videos for human identification. In GaitFi, Channel State Information (CSI) that reflects the multi-path propagation of WiFi is collected to capture human gaits, while videos are captured by cameras. To learn robust gait information, we propose a Lightweight Residual Convolution Network (LRCN) as the backbone network, and further propose the two-stream GaitFi by integrating WiFi and vision features for the gait retrieval task. The GaitFi is trained by the triplet loss and classification loss on different levels of features. Extensive experiments are conducted in the real world, which demonstrates that the GaitFi outperforms state-of-the-art gait recognition methods based on single WiFi or camera, achieving 94.2% for human identification tasks of 12 subjects.