nuScenes
A large-scale autonomous driving perception benchmark dataset released by Motional (formerly nuTonomy). It includes multi-camera, LiDAR, and radar data and is widely used for standardized evaluation of 3D object detection and tracking.
Timeline (last 90 days)
In the long-horizon future extrapolation task on the nuScenes dataset, MESSENGER reduces the 3D endpoint error (EPE3D) by 71.6%.
MESSENGER achieves state-of-the-art performance on nuScenes and Argoverse 2.
nuScenes was released by Motional (formerly nuTonomy) and contains LiDAR and multi-camera data from Boston and Singapore.
A handful of datasets such as ImageNet, nuScenes, KITTI, and Waymo Open Dataset have long dominated evaluation leaderboards for autonomous driving perception, detection, and planning tasks.
The KITTI and nuScenes benchmarks both report detection metrics separately by distance intervals such as 0–30 m, 30–50 m, and 50 m and above.
All Facts (5)
In the long-horizon future extrapolation task on the nuScenes dataset, MESSENGER reduces the 3D endpoint error (EPE3D) by 71.6%.
50%UnverifiedMESSENGER achieves state-of-the-art performance on nuScenes and Argoverse 2.
50%UnverifiednuScenes was released by Motional (formerly nuTonomy) and contains LiDAR and multi-camera data from Boston and Singapore.
50%UnverifiedA handful of datasets such as ImageNet, nuScenes, KITTI, and Waymo Open Dataset have long dominated evaluation leaderboards for autonomous driving perception, detection, and planning tasks.
50%UnverifiedThe KITTI and nuScenes benchmarks both report detection metrics separately by distance intervals such as 0–30 m, 30–50 m, and 50 m and above.
50%