89 datasets found

The dataset used in this paper for autonomous driving lane change decision-making task.

Boreas: A multi-season autonomous driving dataset.

The SynWoodScape dataset consists of 10,000 annotated images captured from four different view angles: Front View (FV), Mirror-View Right (MVR), Mirror-View Left (MVL), and Rear...

The novel dataset for open space segmentation in automotive parking scenarios, containing raw radar echos and their corresponding annotations.

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

The dataset used in this paper for street view synthesis, consisting of large-scale background scenes and foreground moving vehicles.

The dataset used in the paper for automated driving, including scenarios with occluded intersections and merging.

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...

The Argoverse motion forecasting dataset is used to evaluate the proposed method. It contains more than 30K scenarios collected in Pittsburgh and Miami.

The Occ3D-nuScenes dataset is a benchmark for 3D semantic occupancy prediction in autonomous driving, containing 150 validation scenes with 18 semantic classes.

The FLIR ADAS 1 3 dataset contains 10,228 real infrared photos collected in streets and highways of Santa Barbara, USA.

Infrared physical adversarial examples are of great significance for studying the security of infrared AI systems that are widely used in our lives such as autonomous driving....

The CARLA simulator dataset is used for vehicle trajectory control. It contains a test track at ZF Friedrichshafen AG, where the start position is indicated by an arrow and the...

The Cityscapes validation set is a subset of the Cityscapes dataset, containing 500 finely annotated images.

Argoverse 1 Motion Forecasting is a dataset that allows us to train a model on a vast collection of 323, 557 scenarios of 5 seconds each. Each scenario is a 2D bird-eye-view of...

The dataset used in the paper is a simulated on-ramp merge scenario, with 3 vehicles involved. The dataset is used to train a Deep Reinforcement Learning model to learn an...

A self-driving car dataset that captures real-world urban driving in the center of Las Vegas.

The Qcraft dataset is a dataset for autonomous driving tasks.

The dataset used in the paper is a collection of reward functions for autonomous driving, which are designed to evaluate the performance of reinforcement learning agents.

A new performance measure and evaluation benchmark for road detection algorithms.