Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
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Abstract (arXiv)
Smart City applications such as intelligent traffic routing or accident prevention rely on computer vision methods for exact vehicle localization and tracking. Due to the scarcity of accurately labeled data, detecting and tracking vehicles in 3D from multiple cameras proves challenging to explore. We present a massive synthetic dataset for multiple vehicle tracking and segmentation in multiple overlapping and non-overlapping camera views. Unlike existing datasets, which only provide tracking ground truth for 2D bounding boxes, our dataset additionally contains perfect labels for 3D bounding boxes in camera- and world coordinates, depth estimation, and instance, semantic and panoptic segmentation. The dataset consists of 17 hours of labeled video material, recorded from 340 cameras in 64 diverse day, rain, dawn, and night scenes, making it the most extensive dataset for multi-target multi-camera tracking so far. We provide baselines for detection, vehicle re-identification, and single- and multi-camera tracking. Code and data are publicly available.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 36 of its 69 references that are in the map. First posted on arXiv 30 Aug 2022.
Builds on
36 of 69 references.
References · 36
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24 more
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Built on by
Citing papers per year: 2023: 4; 2024: 4; 2025: 3; 2026: 1.
12 papers.
- 2023EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye Viewcited by 33
- 2024Lifting Multi-View Detection and Tracking to the Bird's Eye Viewcited by 25
- 2024SEED4D: A Synthetic Ego--Exo Dynamic 4D Data Generator, Driving Dataset and Benchmarkcited by 8
- 2023So you think you can track?cited by 5
- 2023The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle trackingcited by 3
- 2025RoundaboutHD: High-Resolution Real-World Urban Environment Benchmark for Multi-Camera Vehicle Trackingcited by 3
- 2024City-Scale Multi-Camera Vehicle Tracking System with Improved Self-Supervised Camera Link Modelcited by 2
- 2023SKoPe3D: A Synthetic Dataset for Vehicle Keypoint Perception in 3D from Traffic Monitoring Camerascited by 1
- 2024Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Trackingcited by 1
- 2025TRACER: Efficient Object Re-Identification in Networked Cameras through Adaptive Query Processingcited by 0
- 2025CLIPVehicle: A Unified Framework for Vision-based Vehicle Searchcited by 0
- 2026Beyond the Survey: A Systematic Empirical Study of Detection and Association in Visual MOTcited by 0
- 2026Beyond the Survey: A Systematic Empirical Study of Detection and Association in Visual MOT14 Sep 2026
- 2025CLIPVehicle: A Unified Framework for Vision-based Vehicle Search6 Aug 2025
- 2025TRACER: Efficient Object Re-Identification in Networked Cameras through Adaptive Query Processing13 Jul 2025
- 2025RoundaboutHD: High-Resolution Real-World Urban Environment Benchmark for Multi-Camera Vehicle Tracking11 Jul 2025
- 2024SEED4D: A Synthetic Ego--Exo Dynamic 4D Data Generator, Driving Dataset and Benchmark1 Dec 2024
- 2024Spatial-Temporal Multi-Cuts for Online Multiple-Camera Vehicle Tracking3 Oct 2024
- 2024City-Scale Multi-Camera Vehicle Tracking System with Improved Self-Supervised Camera Link Model18 May 2024
- 2024Lifting Multi-View Detection and Tracking to the Bird's Eye View19 Mar 2024
- 2023EarlyBird: Early-Fusion for Multi-View Tracking in the Bird's Eye View20 Oct 2023
- 2023So you think you can track?13 Sep 2023
- 2023SKoPe3D: A Synthetic Dataset for Vehicle Keypoint Perception in 3D from Traffic Monitoring Cameras4 Sep 2023
- 2023The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle tracking28 Aug 2023