- O
PedX
- opendatalab.com
zipUpdated Apr 23, 2023
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EmailClick to copy linkLink copiedCiteUniversity of Michigan (2023). PedX [Dataset]. https://opendatalab.com/OpenDataLab/PedXzipAvailable download formatsDataset updatedApr 23, 2023Dataset provided byUniversity of MichiganLicenseMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automaticallyDescriptionThe PedX dataset is a large-scale multimodal dataset of pedestrians at complex urban intersections.
The dataset provides high-resolution stereo images, as well as LiDAR data with manually added 2D annotations and automatically added 3D annotations. Additionally, data was collected using two pairs of stereo cameras and four Velodyne LiDAR sensors.
- u
PedX Dataset
- deepblue.lib.umich.edu
ShareFacebookTwitterEmailClick to copy linkLink copiedCiteKim, Wonhui; Ramanagopal, Manikandasriram Srinivasan; Barto, Charles; Yu, Ming-Yuan; Rosaen, Karl; Goumas, Nick; Vasudevan, Ram; Johnson-Roberson, Matthew, PedX Dataset [Dataset]. http://doi.org/10.7302/0fv2-nn47Unique identifierhttps://doi.org/10.7302/0fv2-nn47Dataset provided byDeep Blue DataAuthorsKim, Wonhui; Ramanagopal, Manikandasriram Srinivasan; Barto, Charles; Yu, Ming-Yuan; Rosaen, Karl; Goumas, Nick; Vasudevan, Ram; Johnson-Roberson, MatthewLicenseAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automaticallyTime period coveredNov 30, 2017DescriptionPedX is a large-scale multi-modal collection of pedestrians at complex urban intersections. The dataset provides high-resolution stereo images and LiDAR data with manual 2D and automatic 3D annotations. The data was captured using two pairs of stereo cameras and four Velodyne LiDAR sensors.
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FacebookTwitterEmailMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
The PedX dataset is a large-scale multimodal dataset of pedestrians at complex urban intersections.
The dataset provides high-resolution stereo images, as well as LiDAR data with manually added 2D annotations and automatically added 3D annotations. Additionally, data was collected using two pairs of stereo cameras and four Velodyne LiDAR sensors.