Constructing vectorized high-definition maps from surround-view cameras has garnered significant attention in recent years. However, the commonly employed multi-stage sequential workflow in prevailing approaches often leads to the loss of early-stage information, particularly in perspective-view features. Usually, such loss is observed as an instance missing or shape mismatching in the final birds-eye-view predictions. To address this concern, we propose a novel approach, namely \textbf{HybriMap}, which effectively exploits clues from hybrid features to ensure the delivery of valuable information. Specifically, we design the Dual Enhancement Module, to enable both explicit integration and implicit modification under the guidance of hybrid features. Additionally, the perspective keypoints are utilized as supervision, further directing the feature enhancement process. Extensive experiments conducted on existing benchmarks have demonstrated the state-of-the-art performance of our proposed approach.

利用混合特征构建矢量化的高清地图，提出了一种新颖的方法——HybriMap，有效地利用混合特征的线索，确保宝贵信息的传递，并利用透视关键点作为监督，进一步指导特征增强过程。通过在现有基准测试上进行广泛实验，证明了我们提出的方法的最新性能。

HybriMap：高效矢量化高清地图构建中的混合线索利用