题目:IDDA: a large-scale multi-domain dataset for autonomous driving 名称:IDDA:用于自动驾驶的大规模多域数据集 论文:arxiv.org/abs/2004.0829 主页:idda-dataset.github.io/ IDDA KITTI 题目:Vision meets Robotics: The KITTI Dataset 论文:视觉与机器人技术:KITTI数据集 论文:cvlibs.net/publications 下载...
1. Introduction Autonomous driving has the potential to radically change the cityscape and save many human lives [78]. A crucial part of safe navigation is the detection and track- ing of agents in the environment surrounding the vehicle. To achieve this, a modern self-driving ve...
The method also includes receiving, by the computing system and from the machine-learned retrieval model, a determined current pose value for the vehicle based at least in part on one or more of the pre-localized sensor observations determined to be a closest match to the current sensor ...
Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image-based benchmark datasets have driven development in computer vision tasks such as object detection, tracking and segmentation of agents in the environment. Most autonomous vehicles, however, car...
The First Full-Waveform Flash LiDAR Dataset for Autonomous Vehicle R&D. PixSet Contains Data from a Full AV Sensor Suite (Cameras, LiDARs, Radar, IMU).
In the context of autonomous driving, the existing semantic segmentation concept strongly supports on-road driving where hard inter-class boundaries are enforced and objects can be categorized based on their visible structures with high confidence. Due to the well-structured nature of typical on-road...
Recent re- search has demonstrated that the Vehicle-to-Vehicle (V2V) cooperative perception system has great potential to rev- olutionize the autonomous driving industry. However, the lack of a real-world dataset hinders the progress of this field. ...
18_scenario_4_pedestrian is another example showing the ScenarioID of a collision scenario, which indicates that the autonomous vehicle collided with a pedestrian. The corresponding scenario file can be located at ./greedy-strategy/reward-dto/road1-rain_day-scenarios/18_scenario_4_pedestrian.deep...
To ensure the traceability, reproducibility and standardization for all ML datasets and models generated and consumed within Toyota Research Institute (TRI), we developed the Dataset-Governance-Policy (DGP) that codifies the schema and maintenance of all TRI's Autonomous Vehicle (AV) datasets. Compone...
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has demonstrated that the Vehicle-to-Vehicle (V2V) cooperative perception...