99 datasets found

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.

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.

A light-weight semantic map for visual localization in autonomous driving tasks.

Woodscape is a multi-task, multi-camera fisheye dataset for autonomous driving.

SemanticKITTI: A dataset for semantic scene understanding of lidar sequences.

Semantic segmentation of point clouds is a key component of scene understanding for robotics and autonomous driving. In this paper, we introduce TORNADO-Net - a neural network...

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

A motion and accident prediction benchmark for v2x autonomous driving

Argoverse 2 challenge on 4D occupancy forecasting at the workshop on autonomous driving

Real-time semantic segmentation is playing a more important role in computer vision, due to the growing demand for mobile devices and autonomous driving. Therefore, it is very...