Topological Map Extraction from Overhead Images
Zuoyue Li, Jan Dirk Wegner, Aur\'elien Lucchi

TL;DR
PolyMapper is a novel end-to-end model that directly extracts topological maps, including building footprints and road networks, from overhead images, bypassing pixel-wise segmentation and closely matching existing map structures.
Contribution
The paper introduces PolyMapper, a new approach that predicts vector-based topological maps directly from aerial images, including a novel sequentialization method for graph representation.
Findings
Achieves high accuracy in extracting building footprints and road networks.
Performs well on large-scale datasets, closely matching existing map services.
Outperforms state-of-the-art methods in topological map extraction.
Abstract
We propose a new approach, named PolyMapper, to circumvent the conventional pixel-wise segmentation of (aerial) images and predict objects in a vector representation directly. PolyMapper directly extracts the topological map of a city from overhead images as collections of building footprints and road networks. In order to unify the shape representation for different types of objects, we also propose a novel sequentialization method that reformulates a graph structure as closed polygons. Experiments are conducted on both existing and self-collected large-scale datasets of several cities. Our empirical results demonstrate that our end-to-end learnable model is capable of drawing polygons of building footprints and road networks that very closely approximate the structure of existing online map services, in a fully automated manner. Quantitative and qualitative comparison to the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAutomated Road and Building Extraction · Advanced Image and Video Retrieval Techniques · Remote Sensing and LiDAR Applications
