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KITTI-semantics
创建来自Hello Dataset / Robert
概要
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Overview

This is the KITTI semantic instance segmentation benchmark. It consists of 200 semantically annotated train as well as 200 test images corresponding to the KITTI Stereo and Flow Benchmark 2015.

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:

@ARTICLE{[Alhaija2018IJCV](http://www.cvlibs.net/publications/Alhaija2018IJCV.pdf),
 author = {Hassan Alhaija and Siva Mustikovela and [Lars Mescheder](http://avg.is.tuebingen.mpg.de/person/lmescheder)
and [Andreas Geiger](http://www.cvlibs.net/) and Carsten Rother},
 title = {Augmented Reality
Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes},
 journal = {International Journal of Computer Vision (IJCV)},
 year = {2018}
}

License

CC BY-NC-SA 3.0

数据集信息
应用场景Autonomous Driving
标注类型Semantic Segmentation 2DInstance Segmentation 2D
LicenseCC BY-NC-SA 3.0
更新时间2021-03-24 22:52:21
数据概要
数据格式Image
数据数量400
文件大小313KB
标注数量0
版权归属方
Max Planck Institute for Intellgent Systems
标注方
未知
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