CVC-07: DPM Virtual-World Pedestrian Dataset

Date:26 Apr, 2016

CVC-07: DPM Virtual-World Pedestrian Dataset

    CVC09_FIR_Crops

    This dataset contains 2534 pedestrian images and 2000 background images. The pedestrian images have frontal view and left view, which are annotated as ‘M’ and ‘L’. You may flip the pedestrians to get right view examples. Part annotations are also provided.

    Disclaimer: Please, read the terms of use before downloading the dataset.
    When using this dataset in your research, we will be happy if you cite us

    • Advantages of highly aligned (views and parts) training data:
      • J. Xu, D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa, Learning a Part-based Pedestrian Detector in Virtual World. In IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2014.
    • Domain adaptation of DPM (virtual to real included):
      • J. Xu, S. Ramos, D. Vazquez, & A. M. Lopez, Domain Adaptation of Deformable Part-Based Models. In IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2014.
    • Domain adaptation of with active learning (especial focus on HOG and LBP):
      • D. Vázquez, J. Marín, A.M. López, D. Ponsa and D. Gerónimo, Virtual and Real World Adaptation for Pedestrian Detection. In IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2014.


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