74 datasets found

The dataset used in the paper is a large-scale point cloud compression framework, which can organize sparse and un-structured point clouds in a memory-efficient way.

A real-world stereo dataset collected by robot teleoperation.

A real-world stereo dataset containing both indoor and outdoor environments via robot teleoperation.

The dataset is a real-world dataset for motion prediction in autonomous driving, containing 18-dimensional feature vectors describing the current traffic situation.

The dataset is a synthetic dataset for motion prediction, and a real-world dataset for motion prediction in autonomous driving.

A new dataset for pedestrian action prediction, extending the nuScenes dataset with 3D bounding box and behavioral annotations.

Predicting the future trajectories of pedestrians on the road is an important task for autonomous driving. The pedestrian trajectory prediction is affected by scene paths,...

AmodalSynthDrive is a synthetic multi-task multi-modal amodal perception dataset for autonomous driving. It provides multi-view camera images, 3D bounding boxes, LiDAR data, and...

The highD dataset is a real-world high-definition video dataset of naturalistic vehicle trajectories on German highways.

The dataset is used for lane detection in highway and city scenes.

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 Shifts Vehicle Motion Prediction dataset consists of scenes spanning six locations, three seasons, three times of day, and four weather conditions.

A large-scale dataset for autonomous driving and monocular 3D object detection

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

The comma2k19 dataset is used to evaluate the robustness of lane detection models under physical-world adversarial attacks in autonomous driving.

The TuSimple Lane Detection Challenge dataset is used to evaluate the robustness of lane detection models under physical-world adversarial attacks in autonomous driving.

Scalability in perception for autonomous driving: Waymo open dataset.

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...

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.

A dataset for autonomous driving.