multi-modal fusion is a fundamental task for the perception of an autonomous
driving system, which has recently intrigued many researchers. However,
achieving a rather good performance is not an easy task due to the noisy raw
data, underutilized information, and the misalignment of mul
本文介绍了自动驾驶所使用的流行传感器、它们的数据性质以及相应的目标检测算法。还讨论了用于评估多模态 3D 目标检测算法的现有数据集。接着对基于多模态融合的 3D 检测网络进行了回顾,并介绍了它们的融合阶段、融合输入和融合粒度以及这些设计选择如何随着时间和技术而演变。最后讨论了面临的挑战以及可能的解决方案。希望本文能帮助研究人员了解多模态 3D 目标检测领域并进行相关研究。