Zero-VIRUS*: Zero-shot Vehicle Route Understanding System for Intelligent Transportation
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020, 2020-June, pp. 2534-2543
- Issue Date:
- 2020-07-28
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Filename | Description | Size | |||
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09151032.pdf | Published version | 2.66 MB |
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Nowadays, understanding the traffic statistics in real city-scale camera networks takes an important place in the intelligent transportation field. Recently, vehicle route understanding brings a new challenge to the area. It aims to measure the traffic density by identifying the route of each vehicle in traffic cameras. This year, the AI City Challenge holds a competition with real-world traffic data on vehicle route understanding, which requires both efficiency and effectiveness. In this work, we propose Zero-VIRUS, a Zeroshot VehIcle Route Understanding System, which requires no annotation for vehicle tracklets and is applicable for the changeable real-world traffic scenarios. It adopts a novel 2D field modeling of pre-defined routes to estimate the proximity and completeness of each track. The proposed system has achieved third place on Dataset A in stage 1 of the competition (Track 1: Vehicle Counts by Class at Multiple Intersections) against world-wide participants on both effectiveness and efficiency, with a record of the top place on 50% of the test set.
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