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Found 10 papers, 1 papers with code
DREAM-PCD: Deep Reconstruction and Enhancement of mmWave Radar Pointcloud
However, existing methods failed to simultaneously address the three main challenges in mmWave radar pointcloud reconstruction: specular information lost, low angular resolution, and strong interference and noise.
RFPose-OT: RF-Based 3D Human Pose Estimation via Optimal Transport Theory
Different from existing methods that predict human poses from RF signals on the signal level directly, we consider the structure difference between the RF signals and the human poses, propose to transform the RF signals to the pose domain on the feature level based on Optimal Transport (OT) theory, and generate human poses from the transformed features.
RFMask: A Simple Baseline for Human Silhouette Segmentation with Radio Signals
To overcome such limitations, in this paper, we propose to utilize the radio signals, which can traverse obstacles and are unaffected by the lighting conditions to achieve silhouette segmentation.
Multi-Person Passive WiFi Indoor Localization with Intelligent Reflecting Surface
The past years have witnessed increasing research interest in achieving passive human localization with commodity WiFi devices.
Radio-Assisted Human Detection
In this paper, we propose a radio-assisted human detection framework by incorporating radio information into the state-of-the-art detection methods, including anchor-based onestage detectors and two-stage detectors.
Contactless Electrocardiogram Monitoring with Millimeter Wave Radar
Specifically, we develop a millimeter-wave radar system to contactlessly measure cardiac mechanical activity and reconstruct ECG without any contact in.
RFGAN: RF-Based Human Synthesis
To the best of our knowledge, this is the first work to generate optical images based on RF signals.
High-Resolution WiFi Imaging with Reconfigurable Intelligent Surfaces
Thus, in this paper, we propose a RIS-aided WiFi imaging framework to achieve high-resolution imaging with the off-the-shelf WiFi devices.
Unsupervised Domain Adaptation for Device-free Gesture Recognition
To tackle this challenge, we propose an unsupervised domain adaptation framework for device free gesture recognition by making effective use of the unlabeled target domain data.
Towards Domain-Independent and Real-Time Gesture Recognition Using mmWave Signal
To enhance the robustness of the system and reduce data collecting efforts, we design a data augmentation framework for mmWave signals based on correlations between signal patterns and gesture variations.
