Efficient Cross-Country Data Acquisition Strategy for ADAS via Street-View Imagery

• URL: http://arxiv.org/abs/2602.01836v1
• Date: Mon, 02 Feb 2026 09:09:07 GMT
• Title: Efficient Cross-Country Data Acquisition Strategy for ADAS via Street-View Imagery
• Authors: Yin Wu, Daniel Slieter, Carl Esselborn, Ahmed Abouelazm, Tsung Yuan Tseng, J. Marius Zöllner,
• Abstract summary: We propose a street-view-guided data acquisition strategy that leverages publicly available imagery to identify places of interest (POI)<n>Experiments on traffic sign detection, a task particularly sensitive to cross-country variations in sign appearance, show that our approach achieves performance comparable to random sampling.<n>These results highlight the potential of street-view-guided data acquisition for efficient and cost-effective cross-country model adaptation.
• Score: 9.47955022914982
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Deploying ADAS and ADS across countries remains challenging due to differences in legislation, traffic infrastructure, and visual conventions, which introduce domain shifts that degrade perception performance. Traditional cross-country data collection relies on extensive on-road driving, making it costly and inefficient to identify representative locations. To address this, we propose a street-view-guided data acquisition strategy that leverages publicly available imagery to identify places of interest (POI). Two POI scoring methods are introduced: a KNN-based feature distance approach using a vision foundation model, and a visual-attribution approach using a vision-language model. To enable repeatable evaluation, we adopt a collect-detect protocol and construct a co-located dataset by pairing the Zenseact Open Dataset with Mapillary street-view images. Experiments on traffic sign detection, a task particularly sensitive to cross-country variations in sign appearance, show that our approach achieves performance comparable to random sampling while using only half of the target-domain data. We further provide cost estimations for full-country analysis, demonstrating that large-scale street-view processing remains economically feasible. These results highlight the potential of street-view-guided data acquisition for efficient and cost-effective cross-country model adaptation.

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