Beyond Chamfer Distance: Granular Order-aware Evaluation Metric For Online Mapping
Online map estimation is a crucial component of autonomous driving systems that reduces the reliance on costly high-definition maps. State-of-the-art (SOTA) methods commonly predict map elements as ordered sequences of points that form polylines and polygons. The evaluation of these methods relies predominantly on mean average precision (mAP) based on thresholded Chamfer distance (CD). This framework lacks sensitivity to point ordering and provides limited granularity in assessing geometric quality, making it difficult to distinguish which methods truly excel over others. In this work, we address these limitations on two fronts. For the single-instance similarity measure, we introduce seq...
| Authors | Chouaib Bencheikh Lehocine, Adam Lilja, Junsheng Fu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
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