152 datasets found

A LiDAR simulator for autonomous driving that generates annotated point cloud data.

Scalability in perception for autonomous driving: Waymo open dataset.

The ScribbleKITTI dataset is a dataset for weakly-supervised LiDAR semantic segmentation. It consists of a subset of the SemanticKITTI dataset with weak labels.

The dataset used in the paper is a driving simulator dataset, where the robot and human interact in a driving scenario. The dataset is used to evaluate the performance of the...

The KITTI dataset is a large-scale dataset for autonomous driving, consisting of 15,000 images with annotated objects.

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...

A dataset of on-road naturalistic driving data collected on the 4th Ring Road in Beijing, containing samples of lane changes to the left and right lanes, and car followings.

The dataset used in the paper is the Lyft Motion Prediction Dataset, which contains samples of real-world driving on a complex, urban route in Palo Alto, California.

A dataset for autonomous driving.

The Automotive Radar Dataset is a dataset containing data collected from a scanning Navtech radar in various weather conditions.

RADIATE is a radar dataset for automotive perception in bad weather, including 3 hours of annotated radar images with over 200K labelled road actors.

A driving scenario QA task and a dataset of 160k QA pairs derived from 10k driving scenarios, paired with high quality control commands collected with RL agent and question...

The dataset used in this paper is a real-world driving dataset, which is used to evaluate the performance of the proposed traffic scene generation framework.

The DeFIX dataset is generated by driving a rule-based CARLA autopilot to train an Imitation Learning agent.

The BDD100K MOTS dataset is a subset of the BDD100K dataset, containing 154 videos with annotation for training and validation, and 37 videos for testing.

The ApolloScape dataset is a large-scale dataset for autonomous driving, containing images and annotations.

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

The dataset used for training and testing the proposed EDNet model for efficient disparity estimation.

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...