49 citations · 172 across the 13 of their papers we have counts for
5 papers · 1 filter
Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusion
Minkyoung Cho, Yulong Cao, Jiachen Sun +5
An important paradigm in 3D object detection is the use of multiple modalities to enhance accuracy in both normal and challenging conditions, particularly for long-tail scenarios.…
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency
Minkyoung Cho, Yulong Cao, Zixiang Zhou +1
Deep neural networks (DNNs) are increasingly integrated into LiDAR (Light Detection and Ranging)-based perception systems for autonomous vehicles (AVs), requiring robust performanc…
CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang +3
Perception is crucial in the realm of autonomous driving systems, where bird's eye view (BEV)-based architectures have recently reached state-of-the-art performance. The desirabili…
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun, Weili Nie, Zhiding Yu +2
3D Point cloud is becoming a critical data representation in many real-world applications like autonomous driving, robotics, and medical imaging. Although the success of deep learn…
Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models
Won Park, Nan Liu, Qi Alfred Chen +1
A critical aspect of autonomous vehicles (AVs) is the object detection stage, which is increasingly being performed with sensor fusion models: multimodal 3D object detection models…