46 datasets found

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the SHIFT and Berkeley DeepDrive Attention (BDD-A) datasets.

The dataset used for training and evaluation of the proposed framework for unsupervised metric relocalization.

Oxford RobotCar dataset contains a large amount of data collected from one route through central Oxford, and covers various weather and traffic conditions.

Scalability in perception for autonomous driving: Waymo open dataset.

Image segmentation and depth estimation are crucial tasks in computer vision, especially in autonomous driving scenarios.

The KITTI 3D dataset consists of 7,481 images for training and 7,518 images for testing. The labels of the train set are publicly available and the labels of the test set are...

The Argoverse dataset is a large dataset of real-world outdoor driving scenes.

The KITTI benchmark dataset is used to evaluate the performance of the proposed method. The dataset contains large-scale outdoor sequences of images captured by a forward-facing...

LidarDM: A novel layout-conditioned latent diffusion model for generating realistic LiDAR point clouds.

The Oxford Radar RobotCar dataset is a radar extension to the Oxford RobotCar dataset, containing radar observations of a vehicle in various scenarios.

Novel View Synthesis (NVS) for street scenes in autonomous driving scenarios.

The dataset used in the paper is a collection of images and corresponding affordances (pedestrian hazard, vehicle hazard, red traffic light, and relative heading angle) for...

Scalability in perception for autonomous driving: Waymo open dataset.

The KITTI-360 dataset is an extension of the KITTI dataset, containing 10 new sequences recorded in 2013, with a focus on 360-degree views.

The Argoverse dataset includes 65 training and 24 validation sequences recorded in Miami and Pittsburgh.

Lidar panoptic segmentation for autonomous driving

The WOMD dataset is a large-scale interactive motion forecasting dataset for autonomous driving, which includes 2 million agents and 6 motion trajectories for 8 seconds in the...

A new dataset for omnipotent city understanding from satellite and street-level images of multiple views.

The dataset used in the paper is a large-scale dataset for autonomous driving and UAV racing, generated using the Sim4CV simulator.

The Waymo Open Dataset and the nuScenes Dataset are used to evaluate the performance of the AFDetV2 model.