3D Object Detector

3D object detection aims to accurately identify and locate objects within three-dimensional space, primarily using LiDAR point cloud data and, increasingly, multimodal data fusion with cameras. Current research emphasizes improving accuracy and efficiency through novel architectures like transformers and attention mechanisms, addressing challenges such as data scarcity via techniques like self-supervised learning, active learning, and pseudo-label generation from various sources (e.g., other vehicles' predictions). This field is crucial for autonomous driving and robotics, with advancements directly impacting the safety and reliability of these systems.