FlexMap: Generalized HD Map Construction from Flexible Camera Configurations
Run Wang, Chaoyi Zhou, Amir Salarpour, Xi Liu, Zhi-Qi Cheng, Feng Luo, Mert D. Pes\'e, Siyu Huang

TL;DR
FlexMap is a flexible HD map construction method that adapts to various camera setups without retraining, using a geometry-aware model with implicit 3D understanding and view-adaptive attention.
Contribution
It introduces a novel approach that eliminates explicit geometric projections, enabling adaptable HD map construction across different camera configurations without architectural changes.
Findings
Outperforms existing methods across multiple camera configurations.
Robust to missing views and sensor variations.
Maintains high accuracy without per-configuration retraining.
Abstract
High-definition (HD) maps provide essential semantic information of road structures for autonomous driving systems, yet current HD map construction methods require calibrated multi-camera setups and either implicit or explicit 2D-to-BEV transformations, making them fragile when sensors fail or camera configurations vary across vehicle fleets. We introduce FlexMap, unlike prior methods that are fixed to a specific N-camera rig, our approach adapts to variable camera configurations without any architectural changes or per-configuration retraining. Our key innovation eliminates explicit geometric projections by using a geometry-aware foundation model with cross-frame attention to implicitly encode 3D scene understanding in feature space. FlexMap features two core components: a spatial-temporal enhancement module that separates cross-view spatial reasoning from temporal dynamics, and a…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Advanced Vision and Imaging · 3D Surveying and Cultural Heritage
