Argoverse

doi:doi:10.57702/mxwdcs8c

Argoverse

The Argoverse dataset is a large-scale dataset for autonomous driving, containing 3D point clouds, semantic segmentation masks, and instance segmentation masks.

BibTex:

@dataset{Ming-Fang_Chang_and_John_Lambert_and_Patsorn_Sangkloy_and_Jagjeet_Singh_and_Slawomir_Bak_and_Andrew_Hartnett_and_De_Wang_and_Peter_Carr_and_Simon_Lucey_and_Deva_Ramanan_and_James_Hays_2024,
    abstract = {The Argoverse dataset is a large-scale dataset for autonomous driving, containing 3D point clouds, semantic segmentation masks, and instance segmentation masks.},
    author = {Ming-Fang Chang and John Lambert and Patsorn Sangkloy and Jagjeet Singh and Slawomir Bak and Andrew Hartnett and De Wang and Peter Carr and Simon Lucey and Deva Ramanan and James Hays},
    doi = {10.57702/mxwdcs8c},
    institution = {No Organization},
    keyword = {'3D Forecasting', '3D Scene Flow', '3D Tracking', '3D point cloud', '3D point clouds', '3D tracking', 'Argoverse', 'Autonomous Driving', 'Autonomous Vehicles', 'Autonomous driving', 'BEV semantic occupancy', 'LiDAR Point Clouds', 'Miami', 'Motion Forecasting', 'Motion Prediction', 'Pittsburgh', 'Real-world dataset', 'Rich Maps', 'Safety', 'Scene understanding', 'Self-Driving', 'Trajectory Sequences', 'autonomous driving', 'computer vision', 'forecasting', 'instance segmentation', 'monocular image', 'rich maps', 'road layout estimation', 'semantic segmentation', 'trajectory', 'vehicle occupancy estimation'},
    month = {dec},
    publisher = {TIB},
    title = {Argoverse},
    url = {https://service.tib.eu/ldmservice/dataset/argoverse},
    year = {2024}
}