5 papers
GhostPoint: Self-Supervised Representation Learning by Hallucinating Occluded LiDAR Structure
Mohamed Abdelsamad, Bin Yang, Michael Ulrich +4
3D object detection from LiDAR point clouds is a core problem in autonomous driving. Recent advances in self-supervised learning (SSL) enable scalable pretraining and transfers wel…
SkyShield: Occupancy as a Safety Interface for Low-Altitude UAV Autonomy
Jie Gao, Jie Ma, Kaihui Lin +4
For low-altitude Unmanned Aerial Vehicle (UAV) autonomy, 3D spatial understanding is not merely a perception objective, but the safety interface between human instructions and phys…
Towards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds
Bin Yang, Mohamed Abdelsamad, Miao Zhang +1
Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Existing approaches emphasize seman…
Class-Aware PillarMix: Can Mixed Sample Data Augmentation Enhance 3D Object Detection with Radar Point Clouds?
Miao Zhang, Sherif Abdulatif, Benedikt Loesch +2
Due to the significant effort required for data collection and annotation in 3D perception tasks, mixed sample data augmentation (MSDA) has been widely studied to generate diverse…
Exploring Domain Shift on Radar-Based 3D Object Detection Amidst Diverse Environmental Conditions
Miao Zhang, Sherif Abdulatif, Benedikt Loesch +3
The rapid evolution of deep learning and its integration with autonomous driving systems have led to substantial advancements in 3D perception using multimodal sensors. Notably, ra…