Argoverse 2

doi:doi:10.57702/x1vcc76y

Argoverse 2

The Argoverse 2 motion forecasting dataset contains 250,000 driving scenarios, each 11 seconds long. These scenarios cover 6 geographical regions and represent 763 total hours of driving.

BibTex:

@dataset{Benjamin_Wilson_and_William_Qi_and_Tanmay_Agarwal_and_John_Lambert_and_Jagjeet_Singh_and_Siddhesh_Khandelwal_and_Bowen_Pan_and_Ratnesh_Kumar_and_Andrew_Hartnett_and_Jhony_Kaesemodel_Pontes_and_Deva_Ramanan_and_Peter_Carr_and_James_Hays_2024,
    abstract = {The Argoverse 2 motion forecasting dataset contains 250,000 driving scenarios, each 11 seconds long. These scenarios cover 6 geographical regions and represent 763 total hours of driving.},
    author = {Benjamin Wilson and William Qi and Tanmay Agarwal and John Lambert and Jagjeet Singh and Siddhesh Khandelwal and Bowen Pan and Ratnesh Kumar and Andrew Hartnett and Jhony Kaesemodel Pontes and Deva Ramanan and Peter Carr and James Hays},
    doi = {10.57702/x1vcc76y},
    institution = {No Organization},
    keyword = {'3D Point Clouds', '3D object detection', 'Argoverse', 'Autonomous Driving', 'Forecasting', 'LiDAR', 'Motion Forecasting', 'Perception', 'Point Clouds', 'Scene Flow', 'Scene Understanding', 'Self-Driving Cars', 'Trajectory Prediction', 'driving scenarios', 'geographical regions', 'long-range perception', 'motion forecasting', 'point cloud'},
    month = {dec},
    publisher = {TIB},
    title = {Argoverse 2},
    url = {https://service.tib.eu/ldmservice/dataset/argoverse-2},
    year = {2024}
}