# Wi-CBR: Salient-aware Adaptive WiFi Sensing for Cross-domain Behavior Recognition

arXiv: https://arxiv.org/abs/2506.11616 · HTML: https://mlsanity.com/paper/2506.11616/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 57 references that are in the map.
- First posted on arXiv 13 Jun 2025.

## Builds on (most cited first, 8 of 8)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Group Normalization](https://mlsanity.com/paper/1803.08494/) (2018)
- [Human Action Recognition from Various Data Modalities: A Review](https://mlsanity.com/paper/2012.11866/) (2020)
- [WiGest: A Ubiquitous WiFi-based Gesture Recognition System](https://mlsanity.com/paper/1501.04301/) (2015)
- [WiOpen: A Robust Wi-Fi-based Open-set Gesture Recognition Framework](https://mlsanity.com/paper/2402.00822/) (2024)
- [Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation](https://mlsanity.com/paper/2411.16810/) (2024)
- [Domain Generalization for Face Anti-spoofing via Content-aware Composite Prompt Engineering](https://mlsanity.com/paper/2504.04470/) (2025)
- [Style Evolving along Chain-of-Thought for Unknown-Domain Object Detection](https://mlsanity.com/paper/2503.09968/) (2025)

## Built on by (most cited first, 4 of 4)

- [Cross-Domain Multi-Person Human Activity Recognition via Near-Field Wi-Fi Sensing](https://mlsanity.com/paper/2510.17816/) (2025)
- [Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers](https://mlsanity.com/paper/2605.00869/) (2026)
- [Zero-Fi: Zero-Shot Wi-Fi-Based Human Activity Recognition via Contrastive Signal-Language Alignment](https://mlsanity.com/paper/2607.26381/) (2026)
- [FSTC-Encoder: Feature--Spatial--Temporal Correlation Learning for Generalizable RF Sensing](https://mlsanity.com/paper/2608.08439/) (2026)

## Abstract (arXiv)

The challenge in WiFi-based cross-domain Behavior Recognition lies in the significant interference of domain-specific signals on gesture variation. However, previous methods alleviate this interference by mapping the phase from multiple domains into a common feature space. If the Doppler Frequency Shift (DFS) signal is used to dynamically supplement the phase features to achieve better generalization, it enables the model to not only explore a wider feature space but also to avoid potential degradation of gesture semantic information. Specifically, we propose a novel Salient-aware Adaptive WiFi Sensing for Cross-domain Behavior Recognition (Wi-CBR), which constructs a dual-branch self-attention module that captures temporal features from phase information reflecting dynamic path length variations while extracting kinematic features from DFS correlated with motion velocity. Moreover, we design a Saliency Guidance Module that employs group attention mechanisms to mine critical activity features and utilizes gating mechanisms to optimize information entropy, facilitating feature fusion and enabling effective interaction between salient and non-salient behavioral characteristics. Extensive experiments on two large-scale public datasets (Widar3.0 and XRF55) demonstrate the superior performance of our method in both in-domain and cross-domain scenarios.