152 datasets found

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

NVRadarNet: Real-Time Radar Obstacle and Free Space Detection for Autonomous Driving

The nuScenes dataset is a large-scale dataset for autonomous driving, containing 100,000 scenes with 10 Hz sampling frequency.

The Apolloscape dataset is a large-scale dataset for autonomous driving, containing 75 scenarios with 10 Hz sampling frequency.

LiDAR simulation aims at generating realistic LiDAR data with labels for training and verifying self-driving algorithms more efficiently.

The Waymo Open dataset is a large-scale video dataset used for testing object-centric video models.

Panoptic nuScenes is a multimodal dataset for lidar panoptic segmentation and tracking.

LiDAR segmentation is crucial for autonomous driving systems. The recent range-view approaches are promising for real-time processing. However, they suffer inevitably from...

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.

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

The NuPlan dataset is a closed-loop motion planning benchmark for autonomous vehicles.

The Temporal Occupancy Flow Graph (TOFG) is a unified environment representation that unifies the map information and vehicle trajectories in a homogeneous graph.

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

The A9-Intersection dataset is a real-world dataset made of two RSUs positioned at 7 meters height in an intersection in Garching, Germany. Each RSU has an Ouster OS1-64 LiDAR...

The V2X-Sim 2.0 dataset is a synthetic dataset made with CARLA, containing 100 sequences, each of which has 100 samples containing point clouds obtained by 1 RSU positioned at...

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.

Moving Object Detection (MOD) dataset for fisheye cameras, focusing on autonomous driving scenes.