The Multi Vehicle Stereo Event Camera (MVSEC) dataset is a collection of data designed for the development of novel 3D perception algorithms for event based cameras. Stereo event data is collected from car, motorbike, hexacopter and handheld data, and fused with lidar, IMU, motion capture and GPS to provide ground truth pose and depth images.
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The Argoverse 2 Lidar Dataset is a collection of 20,000 scenarios with lidar sensor data, HD maps, and ego-vehicle pose. It does not include imagery or 3D annotations. The dataset is designed to support research into self-supervised learning in the lidar domain, as well as point cloud forecasting.
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The Argoverse 2 Map Change Dataset is a collection of 1,000 scenarios with ring camera imagery, lidar, and HD maps. Two hundred of the scenarios include changes in the real-world environment that are not yet reflected in the HD map, such as new crosswalks or repainted lanes. By sharing a map dataset that labels the instances in which there are discrepancies with sensor data, we encourage the development of novel methods for detecting out-of-date map regions.
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