3D Detector

3D object detection aims to accurately identify and locate objects in three-dimensional space, a crucial task for autonomous vehicles and robotics. Current research emphasizes improving efficiency (e.g., through token compression in Vision Transformer-based models), robustness (e.g., via cross-weather knowledge distillation and adversarial training), and data efficiency (e.g., using weakly supervised or semi-supervised learning with limited annotations, including coarse clicks or 2D labels). These advancements are vital for deploying reliable 3D detectors in real-world applications, particularly in autonomous driving where safety and accuracy are paramount.