67 datasets found

The ROAD-R dataset contains autonomous driving scenarios with logical requirements.

Nuscenes is a large-scale autonomous driving dataset that provides high-resolution BEV semantic occupancy labels for roads and vehicles.

Neural Radiance Fields (NeRFs) have emerged as promising tools for advancing autonomous driving (AD) research, offering scalable closed-loop simulation and data augmentation...

KITTI 3D object detection dataset, containing 7481 training images and 7518 testing images.

The Waymo Open Dataset and the Waymo Open Motion Dataset are used in this paper.

The dataset used in this paper is a real-world vehicle point cloud collected from a real vehicle self-driving process.

Argoverse2 is an open-source evolution of the original Argoverse

Openlane and Argoverse2 are public datasets used in autonomous driving

Waymo Open Dataset (validation set)

Large dataset for stereo matching, optical flow, and scene flow estimation

Video object segmentation is a fundamental task in many important areas such as autonomous driving, robotic manipulation, video surveillance, and video editing.

The dataset used in the paper is the NuScenes dataset, which contains LiDAR point clouds and corresponding semantic annotations.

KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.

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

A multi-modal dataset capturing self-driving scenes in various conditions, including different times of day and weather.

Multi-agent collaborative perception dataset and benchmark for autonomous driving

Vehicle-infrastructure cooperative 3D object detection dataset

The VoxelNet dataset is a large-scale dataset for 3D object detection, consisting of 3D point clouds and corresponding annotations.

The Multi-View 3D Object Detection Network is a dataset for 3D object detection, consisting of 3D point clouds and corresponding annotations.

The KITTI benchmark suite is a large-scale dataset for 3D object detection, consisting of 7,481 training samples and 7,518 test samples.