CrowdNet, Proceedings of the 2016 ACM on Multimedia Conference, MM '16, 2007. ,
DOI : 10.1109/CVPR.2015.7298684
Unsupervised Bayesian Detection of Independent Motion in Crowds, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), 2006. ,
DOI : 10.1109/CVPR.2006.320
Privacy preserving crowd monitoring: Counting people without people models or tracking, 2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008. ,
DOI : 10.1109/CVPR.2008.4587569
Bayesian Poisson regression for crowd counting, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,
DOI : 10.1109/ICCV.2009.5459191
Feature Mining for Localised Crowd Counting, Procedings of the British Machine Vision Conference 2012, 2012. ,
DOI : 10.5244/C.26.21
Multi-column deep neural networks for image classification, CVPR, 2012. ,
Marked point processes for crowd counting, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009. ,
DOI : 10.1109/CVPR.2009.5206621
Deep Residual Learning for Image Recognition, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.770-778, 2016. ,
DOI : 10.1109/CVPR.2016.90
Multi-source Multi-scale Counting in Extremely Dense Crowd Images, 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2007. ,
DOI : 10.1109/CVPR.2013.329
Detecting Humans in Dense Crowds Using Locally-Consistent Scale Prior and Global Occlusion Reasoning, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, issue.10, pp.1986-1998, 2015. ,
DOI : 10.1109/TPAMI.2015.2396051
Counting Pedestrians in Crowds Using Viewpoint Invariant Training, Procedings of the British Machine Vision Conference 2005, 2005. ,
DOI : 10.5244/C.19.63
Learning to count objects in images, NIPS, 2007. ,
Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection, 2008 19th International Conference on Pattern Recognition, 2008. ,
DOI : 10.1109/ICPR.2008.4761705
Feature Pyramid Networks for Object Detection, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. ,
DOI : 10.1109/CVPR.2017.106
Microsoft COCO: Common Objects in Context, ECCV. 7 ,
DOI : 10.1007/978-3-319-10602-1_48
Bayesian Model Adaptation for Crowd Counts, 2015 IEEE International Conference on Computer Vision (ICCV) ,
DOI : 10.1109/ICCV.2015.475
On the efficacy of texture analysis for crowd monitoring, Proceedings SIBGRAPI'98. International Symposium on Computer Graphics, Image Processing, and Vision (Cat. No.98EX237), 1998. ,
DOI : 10.1109/SIBGRA.1998.722773
Learning Deconvolution Network for Semantic Segmentation, 2015 IEEE International Conference on Computer Vision (ICCV), 2015. ,
DOI : 10.1109/ICCV.2015.178
Towards Perspective-Free Object Counting with Deep Learning, ECCV, 2007. ,
DOI : 10.1109/DICTA.2009.22
A mrf-based approach for realtime subway monitoring, CVPR, 2001. ,
Counting Crowded Moving Objects, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 1 (CVPR'06), 2006. ,
DOI : 10.1109/CVPR.2006.92
YOLO9000: Better, Faster, Stronger, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008. ,
DOI : 10.1109/CVPR.2017.690
URL : http://arxiv.org/pdf/1612.08242
Distributed data fusion for real-time crowding estimation, Signal Processing, vol.53, issue.1, pp.47-63, 1996. ,
DOI : 10.1016/0165-1684(96)00075-8
U-Net: Convolutional Networks for Biomedical Image Segmentation, 2015. ,
DOI : 10.1007/978-3-319-24574-4_28
URL : http://arxiv.org/pdf/1505.04597
Crowd Counting Using Multiple Local Features, 2009 Digital Image Computing: Techniques and Applications, 2009. ,
DOI : 10.1109/DICTA.2009.22
Switching Convolutional Neural Network for Crowd Counting, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007. ,
DOI : 10.1109/CVPR.2017.429
URL : http://arxiv.org/pdf/1708.00199
Very deep convolutional networks for large-scale image recognition, 2007. ,
End-to-End People Detection in Crowded Scenes, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. ,
DOI : 10.1109/CVPR.2016.255
URL : http://arxiv.org/pdf/1506.04878
Detecting Pedestrians Using Patterns of Motion and Appearance, International Journal of Computer Vision, vol.20, issue.3, pp.153-161, 2003. ,
DOI : 10.1007/s11263-005-6644-8
URL : http://www.merl.com/papers/docs/TR2003-90.pdf
Deep People Counting in Extremely Dense Crowds, Proceedings of the 23rd ACM international conference on Multimedia, MM '15, 2015. ,
DOI : 10.1109/ICCV.2003.1238663
Automatic adaptation of a generic pedestrian detector to a specific traffic scene, CVPR 2011, 2011. ,
DOI : 10.1109/CVPR.2011.5995698
URL : http://mmlab.ie.cuhk.edu.hk/archive/2011/adaptDet.pdf
Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors, ICCV, 2005. ,
Cross-scene crowd counting via deep convolutional neural networks, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007. ,
DOI : 10.1109/CVPR.2015.7298684
Singleimage crowd counting via multi-column convolutional neural network, 2007. ,
DOI : 10.1109/cvpr.2016.70
Segmentation and Tracking of Multiple Humans in Crowded Environments, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.7, pp.1198-1211, 2008. ,
DOI : 10.1109/TPAMI.2007.70770