异常检测
计算机科学
激光雷达
目标检测
人工智能
雷达
计算机视觉
集合(抽象数据类型)
点(几何)
感知
数据集
国家(计算机科学)
对象(语法)
异常(物理)
遥感
模式识别(心理学)
地理
电信
生物
物理
神经科学
数学
程序设计语言
凝聚态物理
算法
几何学
作者
Daniel Bogdoll,Maximilian Nitsche,J. Marius Zollner
标识
DOI:10.1109/cvprw56347.2022.00495
摘要
Nowadays, there are outstanding strides towards a future with autonomous vehicles on our roads. While the perception of autonomous vehicles performs well under closed-set conditions, they still struggle to handle the unexpected. This survey provides an extensive overview of anomaly detection techniques based on camera, lidar, radar, multimodal and abstract object level data. We provide a systematization including detection approach, corner case level, ability for an online application, and further attributes. We outline the state-of-the-art and point out current research gaps.
科研通智能强力驱动
Strongly Powered by AbleSci AI