论文标题
朝着基于地图的语义分割面具验证
Towards Map-Based Validation of Semantic Segmentation Masks
论文作者
论文摘要
自主驾驶的人工智能必须满足对安全性和鲁棒性的严格要求。我们建议不仅具有给定的地面真相标签，而且还具有额外的A-Priori知识来验证自动驾驶汽车的机器学习模型。特别是，我们建议使用给定的街道地图数据在语义分割面具中验证可驱动的区域。我们提出了第一个结果，这表明可以通过基于地图的验证来发现预测错误。
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness. We propose to validate machine learning models for self-driving vehicles not only with given ground truth labels, but also with additional a-priori knowledge. In particular, we suggest to validate the drivable area in semantic segmentation masks using given street map data. We present first results, which indicate that prediction errors can be uncovered by map-based validation.
