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README.md
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# VVSim Dataset
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**VVSim** is a large-scale dataset created for aerial–ground cooperative perception (AGCP). It integrates synchronized multimodal sensing data and state information collected simultaneously from vehicles and UAVs. The dataset contains **61K** fully annotated frames that cover **19** interaction scenarios (e.g., cut-in and lane change), along with **5** weather conditions (e.g., sunny, foggy, rainy, cloudy, snowy) and **11** scene types such as city, town, university, highway, and mountain environments. Beyond these frames, VVSim provides **255K** LiDAR sweeps and **3.5M** images (e.g., **1.2M** RGB images, **1.2M** semantic segmentation images, and **1.1M** depth images), accompanied by detailed annotations for 2D and 3D bounding boxes, object trajectories, and agent states.
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name: VVSim
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tags:
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- aerial-ground cooperative perception
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- autonomous driving
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- trajectory prediction
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license: CC-BY-4.0
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task_categories:
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- perception
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- planning
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- control
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task_ids:
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- object detection
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# VVSim Dataset
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**VVSim** is a large-scale dataset created for aerial–ground cooperative perception (AGCP). It integrates synchronized multimodal sensing data and state information collected simultaneously from vehicles and UAVs. The dataset contains **61K** fully annotated frames that cover **19** interaction scenarios (e.g., cut-in and lane change), along with **5** weather conditions (e.g., sunny, foggy, rainy, cloudy, snowy) and **11** scene types such as city, town, university, highway, and mountain environments. Beyond these frames, VVSim provides **255K** LiDAR sweeps and **3.5M** images (e.g., **1.2M** RGB images, **1.2M** semantic segmentation images, and **1.1M** depth images), accompanied by detailed annotations for 2D and 3D bounding boxes, object trajectories, and agent states.
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