A. Geiger, P. Lenz, and R. Urtasun, Are we ready for autonomous driving? the kitti vision benchmark suite, Conference on Computer Vision and Pattern Recognition(CVPR), p.6, 2005.

J. H. Hosang, M. Omran, R. Benenson, and B. Schiele, Taking a deeper look at pedestrians. CoRR, 2015.

X. Du, M. El-khamy, J. Lee, and L. S. Davis, Fused dnn: A deep neural network fusion approach to fast and robust pedestrian detection, vol.2, p.6, 2016.

Y. Tian, P. Luo, X. Wang, and X. Tang, Deep learning strong parts for pedestrian detection, Proceedings of the IEEE International Conference on Computer Vision, vol.2, p.6, 2015.

L. Zhang, L. Lin, X. Liang, and K. He, Is faster R-CNN doing well for pedestrian detection?, 2016.

T. Lin, P. Goyal, and R. Girshick, Focal Loss for Dense Object Detection, vol.2017, pp.2999-3007

W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed et al., Ssd: Single shot multibox detector, European Conference on Computer Vision, pp.21-37, 2016.

G. Huang, Z. Liu, K. Q. Weinberger, and L. Van-der-maaten, Densely connected convolutional networks, CVPR, 2004.

C. Szegedy, S. Ioffe, and V. Vanhoucke, Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning, 2016.

T. Lin, Feature pyramid networks for object detection, 2017.

R. Girshick, Fast R-CNN, International Conference on Computer Vision (ICCV), 2015.