Regression Network for Real-Time Pedestrian Detection

[1]  Jun Zhang,et al.  Real-Time Pedestrian Detection in Monitoring Scene Based on Head Model , 2019, ICIC.

[2]  Shuicheng Yan,et al.  Scale-Aware Fast R-CNN for Pedestrian Detection , 2015, IEEE Transactions on Multimedia.

[3]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[4]  Anelia Angelova,et al.  Real-Time Pedestrian Detection with Deep Network Cascades , 2015, BMVC.

[5]  Ross B. Girshick,et al.  Fast R-CNN , 2015, 1504.08083.

[6]  Liang Lin,et al.  Is Faster R-CNN Doing Well for Pedestrian Detection? , 2016, ECCV.

[7]  Xiaogang Wang,et al.  Intelligent multi-camera video surveillance: A review , 2013, Pattern Recognit. Lett..

[8]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[10]  Pietro Perona,et al.  Pedestrian Detection: An Evaluation of the State of the Art , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Bernt Schiele,et al.  Taking a deeper look at pedestrians , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Zhenxue Chen,et al.  Real-time pedestrian detection with deep supervision in the wild , 2019, Signal Image Video Process..

[13]  Pietro Perona,et al.  Fast Feature Pyramids for Object Detection , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.