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FRSign Dataset
2D Box
2D Classification
Autonomous Driving
|...
许可协议: CC-BY-NC-SA 4.0

Overview

FRSign, a large-scale and accurate dataset for vision-based railway traffic light detection and recognition.

It contains more than 100,000 images illustrating six types of French railway traffic lights and their possible color combinations, together with the relevant information regarding their acquisition such as date, time, sensor parameters, and bounding boxes.

Citation

Please use the following citation when referencing the dataset:

@ARTICLE{2020arXiv200205665H,
       author = {{Harb}, Jeanine and {R{\'e}b{\'e}na}, Nicolas and {Chosidow}, Rapha{\"e}l and {Roblin}, Gr{\'e}goire and {Potarusov}, Roman and {Hajri}, Hatem},
        title = "{FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains}",
      journal = {arXiv e-prints},
     keywords = {Computer Science - Computers and Society, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning},
         year = "2020",
        month = "Feb",
          eid = {arXiv:2002.05665},
        pages = {arXiv:2002.05665},
archivePrefix = {arXiv},
       eprint = {2002.05665},
 primaryClass = {cs.CY},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020arXiv200205665H},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

License

You are free to:

  • Share — copy and redistribute the material in any medium or format

  • Adapt — remix, transform, and build upon the material

  • The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

  • NonCommercial — You may not use the material for commercial purposes.

  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

  • You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
  • No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
数据概要
数据格式
image,
数据量
100K
文件大小
--
发布方
Irt Systemx
An Institute for Technological Research (IRT) is an interdisciplinary thematic institute that develops economic sectors related to its field through a balanced strategic public-private partnership. For this, it manages research programs coupled with technology platforms, conducts research and development projects at the international level, contributes to the engineering of initial and continuous trainings (qualifying professional training and/or degree delivering); and ensures the exploitation of the obtained results.
| 数据量 100K | 大小 --
FRSign Dataset
2D Box 2D Classification
Autonomous Driving
许可协议: CC-BY-NC-SA 4.0

Overview

FRSign, a large-scale and accurate dataset for vision-based railway traffic light detection and recognition.

It contains more than 100,000 images illustrating six types of French railway traffic lights and their possible color combinations, together with the relevant information regarding their acquisition such as date, time, sensor parameters, and bounding boxes.

Citation

Please use the following citation when referencing the dataset:

@ARTICLE{2020arXiv200205665H,
       author = {{Harb}, Jeanine and {R{\'e}b{\'e}na}, Nicolas and {Chosidow}, Rapha{\"e}l and {Roblin}, Gr{\'e}goire and {Potarusov}, Roman and {Hajri}, Hatem},
        title = "{FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains}",
      journal = {arXiv e-prints},
     keywords = {Computer Science - Computers and Society, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning},
         year = "2020",
        month = "Feb",
          eid = {arXiv:2002.05665},
        pages = {arXiv:2002.05665},
archivePrefix = {arXiv},
       eprint = {2002.05665},
 primaryClass = {cs.CY},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2020arXiv200205665H},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

License

You are free to:

  • Share — copy and redistribute the material in any medium or format

  • Adapt — remix, transform, and build upon the material

  • The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  • Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

  • NonCommercial — You may not use the material for commercial purposes.

  • ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

  • No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

  • You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
  • No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
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