A regression-based radar-mote system for people counting, Int. Conf. on Pervasive Computing and Communications (PerCom), 2014. ,
Reliable human detection and tracking in top-view depth images, Int, Conf. on Computer Vision and Pattern Recognition Workshops (CVPRW), 2013. ,
SVM based people counting method in the corridor scene using a single-layer laser scanner, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 2016. ,
DOI : 10.1109/ITSC.2016.7795979
Vision-based counting of pedestrians and cyclists, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 2016. ,
DOI : 10.1109/WACV.2016.7477685
Pedestrian counting based on spatial and temporal analysis, 2014 IEEE International Conference on Image Processing (ICIP), 2014. ,
DOI : 10.1109/ICIP.2014.7025492
Stable multi-target tracking in real-time surveillance video, CVPR 2011, 2011. ,
DOI : 10.1109/CVPR.2011.5995667
People counting based on head detection combining Adaboost and CNN in crowded surveillance environment, Neurocomputing, vol.208 ,
DOI : 10.1016/j.neucom.2016.01.097
ImageNet classification with deep convolutional neural networks, Advances in Neural Information Processing Systems (NIPS), 2012. ,
DOI : 10.1162/neco.2009.10-08-881
ImageNet Large Scale Visual Recognition Challenge, International Journal of Computer Vision, vol.1010, issue.1, p.2014 ,
DOI : 10.1007/978-3-642-15555-0_11
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks, Advances in Neural Information Processing Systems (NIPS), 2015. ,
DOI : 10.1109/TPAMI.2016.2577031
R-FCN : object detection via regionbased fully convolutional networks, Advances in Neural Information Processing Systems (NIPS), 2016. ,
, SSD : Single Shot Multibox Detector, European Conference on Computer Vision (ECCV), 2016.
, YOLO9000 : Better, Faster, Stronger, Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2017.
Speed/accuracy trade-offs for modern convolutional object detectors, Int, Conf. on Computer Vision and Pattern Recognition (CVPR), 2017. ,
Simple Online and Realtime Tracking with deep association metric, Int, Conf. on Image Processing (ICIP), 2017. ,
MOT16 : a benchmark for multiobject tracking, p.2016 ,
Visualizing and Understanding Convolutional Networks, European Conference on Computer Vision (ECCV), 2014. ,
DOI : 10.1007/978-3-319-10590-1_53
Deep residual learning for image recognition , Int, Conf. on Computer Vision and Pattern Recognition (CVPR), 2016. ,
Rethinking the Inception architecture for computer vision, Int, Conf. on Computer Vision and Pattern Recognition (CVPR), 2016. ,
MobileNets : efficient convolutional neural networks for mobile vision applications, p.2017 ,