This paper proposes a novel contrastive learning framework, called FOCAL, for extracting
comprehensive features from multimodal time-series sensing signals through self …

Advances in wireless technologies have transformed wireless networks from a pure
communication medium to a pervasive sensing platform, enabling many sensorless and …

In recent years, wireless sensing has attracted lots of research attention with a large range of
applications enabled. However, several critical issues still hinder wireless sensing from …

The perception of autonomous vehicles using radars has attracted increased research
interest due its ability to operate in fog and bad weather. However training radar models is …

This paper introduces a novel framework, ie, RFPose-OT, to enable three-dimensional (3D)
human pose estimation from radio frequency (RF) signals. Different from existing methods …

Millimeter-wave (mmWave) radar has been widely used in wireless sensing due to its non-
contact nature, privacy preservation, and immunity to adverse lighting conditions. However …

Recently, with the advancement of the Internet of Things (IoT), WiFi CSI-based HAR has
gained increasing attention from academic and industry communities. By integrating the …

Advanced human sensing technologies based on radio frequency (RF) signals have gained
widespread attention in recent years. However, due to the sparsity and incompleteness of …

Interference mitigation for automotive radar is becoming increasingly important due to its
increasing popularity in automobiles. In this paper, we tackle this problem and propose two …

Existing RF-based human pose estimation methods usually require intensive computations
and cannot meet the real-time processing and portability requirements for mobile devices …