5 papers
Context-Aware Intelligent Vehicles
Liangkai Liu, Shuyao Shi, Mingke Wang +4
Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-cabin monitoring and fleet ma…
Fleets Need a Context Plane: Rethinking Cooperative Perception for Autonomous Drones
Liangkai Liu, Xiaoxiao Wu
Cooperative perception allows a drone fleet to combine observations from multiple viewpoints. However, existing systems typically fix their feature-sharing policies at design time…
Adversarial Calibration Attack on Autonomous Vehicles
Liangkai Liu, Qingzhao Zhang, Kang G. Shin
Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration, temperature variation, or min…
MM-BEV: Enhancing Timeliness by Computing Where and When it Matters
Liangkai Liu, Kang G. Shin
Multimodal bird's-eye-view (BEV) perception combines LiDAR depth accuracy with dense camera semantics, but its high computational cost and imperfect sensing conditions make real-ti…
AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge
Chao Wu, Yifan Gong, Liangkai Liu +7
Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the d…