Datasets > Modality > Environment > CARLA (Car Learning to Act)

CARLA (Car Learning to Act)

Introduced by Dosovitskiy et al. in CARLA: An Open Urban Driving Simulator

CARLA (CAR Learning to Act) is an open simulator for urban driving, developed as an open-source layer over Unreal Engine 4. Technically, it operates similarly to, as an open source layer over Unreal Engine 4 that provides sensors in the form of RGB cameras (with customizable positions), ground truth depth maps, ground truth semantic segmentation maps with 12 semantic classes designed for driving (road, lane marking, traffic sign, sidewalk and so on), bounding boxes for dynamic objects in the environment, and measurements of the agent itself (vehicle location and orientation).

Source: Synthetic Data for Deep Learning

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