This paper introduces 3D-ASCN, a novel deep learning architecture for point cloud recognition that achieves domain-invariant feature extraction, making it robust to variations in LiDAR sensor configurations and datasets, which is crucial for reliable autonomous driving applications.
PeP는 새로운 점 향상 페인팅 방법과 LM 기반 점 인코더를 포함한 모듈로, 성능이 우수하며 모델에 유연성을 제공합니다.
PePは、点群認識のための新しい手法であり、優れた性能を提供します。
The author introduces the PeP module, combining a refined point painting method and an LM-based point encoder to enhance point cloud recognition tasks, leading to superior performance in semantic segmentation and object detection.