KITTI-road
2D Semantic Segmentation
Autonomous Driving
|...
许可协议: CC BY-NC-SA 3.0

Overview

The road and lane estimation benchmark consists of 289 training and 290 test images. We evaluate road and lane estimation performance in the bird's-eye-view space. It contains different categories of road scenes:

  • uu - urban unmarked (98/100)
  • um - urban marked (95/96)
  • umm - urban multiple marked lanes (96/94)
  • urban - combination of the three above

Data Collection

We equipped a standard station wagon with two high-resolution color and grayscale video cameras. Accurate ground truth is provided by a Velodyne laser scanner and a GPS localization system. Our datsets are captured by driving around the mid-size city of Karlsruhe, in rural areas and on highways. Up to 15 cars and 30 pedestrians are visible per image.

img

Citation

Please use the following citation when referencing the dataset:

@INPROCEEDINGS{Fritsch2013ITSC,
  author = {Jannik Fritsch and Tobias Kuehnl and Andreas Geiger},
  title = {A New Performance Measure and Evaluation Benchmark for Road Detection Algorithms},
  booktitle = {International Conference on Intelligent Transportation Systems (ITSC)},
  year = {2013}
}

License

CC BY-NC-SA 3.0

数据概要
数据格式
Point Cloud, Image,
数据量
579
文件大小
2.18GB
发布方
Max Planck Institute for Intellgent Systems
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems
数据集反馈
| 139 | 数据量 579 | 大小 2.18GB
KITTI-road
2D Semantic Segmentation
Autonomous Driving
许可协议: CC BY-NC-SA 3.0

Overview

The road and lane estimation benchmark consists of 289 training and 290 test images. We evaluate road and lane estimation performance in the bird's-eye-view space. It contains different categories of road scenes:

  • uu - urban unmarked (98/100)
  • um - urban marked (95/96)
  • umm - urban multiple marked lanes (96/94)
  • urban - combination of the three above

Data Collection

We equipped a standard station wagon with two high-resolution color and grayscale video cameras. Accurate ground truth is provided by a Velodyne laser scanner and a GPS localization system. Our datsets are captured by driving around the mid-size city of Karlsruhe, in rural areas and on highways. Up to 15 cars and 30 pedestrians are visible per image.

img

Citation

Please use the following citation when referencing the dataset:

@INPROCEEDINGS{Fritsch2013ITSC,
  author = {Jannik Fritsch and Tobias Kuehnl and Andreas Geiger},
  title = {A New Performance Measure and Evaluation Benchmark for Road Detection Algorithms},
  booktitle = {International Conference on Intelligent Transportation Systems (ITSC)},
  year = {2013}
}

License

CC BY-NC-SA 3.0

数据集反馈
0
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