DuMapper: Towards Automatic Verification of Large-Scale POIs with Street Views at Baidu Maps
Miao Fan, Jizhou Huang, Haifeng Wang

TL;DR
DuMapper is an automated system that leverages street-view images and advanced algorithms to verify large-scale POI data efficiently, reducing costs and increasing verification throughput at Baidu Maps.
Contribution
The paper introduces DuMapper, a novel automatic POI verification system that significantly improves efficiency using multimodal street-view data and ANN search algorithms.
Findings
Increased POI verification throughput by 50 times.
Deployed in production at Baidu Maps since 2021.
Performed over 405 million verification iterations in 3.5 years.
Abstract
With the increased popularity of mobile devices, Web mapping services have become an indispensable tool in our daily lives. To provide user-satisfied services, such as location searches, the point of interest (POI) database is the fundamental infrastructure, as it archives multimodal information on billions of geographic locations closely related to people's lives, such as a shop or a bank. Therefore, verifying the correctness of a large-scale POI database is vital. To achieve this goal, many industrial companies adopt volunteered geographic information (VGI) platforms that enable thousands of crowdworkers and expert mappers to verify POIs seamlessly; but to do so, they have to spend millions of dollars every year. To save the tremendous labor costs, we devised DuMapper, an automatic system for large-scale POI verification with the multimodal street-view data at Baidu Maps. DuMapper…
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Taxonomy
TopicsGeographic Information Systems Studies · Data Management and Algorithms · Human Mobility and Location-Based Analysis
MethodsADaptive gradient method with the OPTimal convergence rate
