130 citations · 525 across the 45 of their papers we have counts for
9 papers · 1 filter
Snoopy: Sniffing Your Smartwatch Passwords via Deep Sequence Learning
Chris Xiaoxuan Lu, Bowen Du, Hongkai Wen +5
Demand for smartwatches has taken off in recent years with new models which can run independently from smartphones and provide more useful features, becoming first-class mobile pla…
Learning Selective Sensor Fusion for States Estimation
Changhao Chen, Stefano Rosa, Chris Xiaoxuan Lu +3
Autonomous vehicles and mobile robotic systems are typically equipped with multiple sensors to provide redundancy. By integrating the observations from different sensors, these mob…
See Through Smoke: Robust Indoor Mapping with Low-cost mmWave Radar
Chris Xiaoxuan Lu, Stefano Rosa, Peijun Zhao +5
This paper presents the design, implementation and evaluation of milliMap, a single-chip millimetre wave (mmWave) radar based indoor mapping system targetted towards low-visibility…
AtLoc: Attention Guided Camera Localization
Bing Wang, Changhao Chen, Chris Xiaoxuan Lu +3
Deep learning has achieved impressive results in camera localization, but current single-image techniques typically suffer from a lack of robustness, leading to large outliers. To…
DeepTIO: A Deep Thermal-Inertial Odometry with Visual Hallucination
Muhamad Risqi U. Saputra, Pedro P. B. de Gusmao, Chris Xiaoxuan Lu +7
Visual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fa…
Milli-RIO: Ego-Motion Estimation with Low-Cost Millimetre-Wave Radar
Yasin Almalioglu, Mehmet Turan, Chris Xiaoxuan Lu +2
Robust indoor ego-motion estimation has attracted significant interest in the last decades due to the fast-growing demand for location-based services in indoor environments. Among…
Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues
Chris Xiaoxuan Lu, Xuan Kan, Bowen Du +5
Facial recognition is a key enabling component for emerging Internet of Things (IoT) services such as smart homes or responsive offices. Through the use of deep neural networks, fa…
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction
Changhao Chen, Chris Xiaoxuan Lu, Bing Wang +2
Dynamical models estimate and predict the temporal evolution of physical systems. State Space Models (SSMs) in particular represent the system dynamics with many desirable properti…
Selective Sensor Fusion for Neural Visual-Inertial Odometry
Changhao Chen, Stefano Rosa, Yishu Miao +4
Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input…