Online High Definition Map (HDMap) estimation from sensors offers a low-cost alternative to manually acquired HDMaps. As such, it promises to lighten costs for already HDMap-reliant Autonomous Driving systems, and potentially even spread their use to new systems. In this paper, we propose to improve online HDMap estimation by accounting for already existing maps. We identify 3 reasonable types of useful existing maps (minimalist, noisy, and outdated). We also introduce MapEX, a novel online HDMap estimation framework that accounts for existing maps. MapEX achieves this by encoding map elements into query tokens and by refining the matching algorithm used to train classic query based map estimation models. We demonstrate that MapEX brings significant improvements on the nuScenes dataset. For instance, MapEX - given noisy maps - improves by 38% over the MapTRv2 detector it is based on and by 16% over the current SOTA.

在线高清地图 (HDMap) 估计通过传感器提供一个低成本的替代手动获取 HDMap 的方法，我们提出通过考虑已有的地图来改进在线 HDMap 估计，并引入 MapEX，一种新颖的在线 HDMap 估计框架，通过将地图元素编码为查询令牌，并改进用于训练经典查询基础地图估计模型的匹配算法，我们在 nuScenes 数据集上证明了 MapEX 能够显著提高性能。

注重地图！在传感器数据估计在线高清地图时考虑现有地图信息