C. Arteta, V. Lempitsky, and A. Zisserman, Counting in the wild, ECCV, 2016.

L. Boominathan, S. S. Srinivas, R. Kruthiventi, and . Babu, Crowdnet: a deep convolutional network for dense crowd counting, ACM MM, 2016.

J. Gabriel, R. Brostow, and . Cipolla, Unsupervised bayesian detection of independent motion in crowds, CVPR, vol.1, 2006.

X. Cao, Z. Wang, Y. Zhao, and F. Su, Scale aggregation network for accurate and efficient crowd counting, ECCV, vol.7, 2006.

B. Antoni, Z. Chan, N. Liang, and . Vasconcelos, Privacy preserving crowd monitoring: Counting people without people models or tracking, CVPR, 2006.

B. Antoni, N. Chan, and . Vasconcelos, Counting people with low-level features and bayesian regression, IEEE Transactions on Image Processing, vol.21, issue.4, pp.2160-2177, 2012.

K. Chen and C. C. Loy, Shaogang Gong, and Tony Xiang. Feature mining for localised crowd counting, BMVC, vol.1, 2012.

N. Dalal and B. Triggs, Histograms of oriented gradients for human detection, CVPR, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548512

L. Fiaschi and U. Köthe, Rahul Nair, and Fred A Hamprecht. Learning to count with regression forest and structured labels, ICPR, vol.1, p.3, 2012.

X. Gao, X. Hou, J. Tang, and H. Cheng, Complete solution classification for the perspective-three-point problem, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.8, pp.930-943, 2003.

S. Huang, X. Li, Z. Zhang, F. Wu, S. Gao et al., Body structure aware deep crowd counting, IEEE Transactions on Image Processing, vol.27, issue.3, pp.1049-1059, 2008.

H. Idrees, I. Saleemi, C. Seibert, and M. Shah, Multi-source multi-scale counting in extremely dense crowd images, CVPR, p.6, 2004.

H. Idrees, K. Soomro, and M. Shah, Detecting humans in dense crowds using locally-consistent scale prior and global occlusion reasoning, TPAMI, vol.37, issue.10, 1986.

Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long et al., Caffe: Convolutional architecture for fast feature embedding, ACM MM, 2014.

D. Kong, D. Gray, and H. Tao, Counting pedestrians in crowds using viewpoint invariant training, BMVC, vol.1, 2005.

V. Lempitsky and A. Zisserman, Learning to count objects in images, NIPS, vol.1, p.3, 2010.

Y. Li, X. Zhang, and D. Chen, Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes, CVPR, 2007.

J. Sheng-fuu-lin, H. Chen, and . Chao, Estimation of number of people in crowded scenes using perspective transformation, TSMC-A, vol.31, issue.6, pp.645-654, 2001.

J. Liu, C. Gao, D. Meng, and A. G. Hauptmann, Decidenet: Counting varying density crowds through attention guided detection and density estimation, CVPR, vol.2, 2018.

X. Liu, J. Weijer, and A. D. Bagdanov, Leveraging unlabeled data for crowd counting by learning to rank, CVPR, 2007.

Y. Liu, M. Shi, Q. Zhao, and X. Wang, Point in, box out: Beyond counting persons in crowds, CVPR, vol.1, 2019.

K. Chen-change-loy and . Chen, Shaogang Gong, and Tao Xiang. Crowd counting and profiling: Methodology and evaluation, Modeling, Simulation and Visual Analysis of Crowds, vol.2, p.3, 2013.

Z. Lu, M. Shi, and Q. Chen, Crowd counting via scale-adaptive convolutional neural network, In WACV, issue.2, 2018.

. An-marana, . Costa, S. A. Lotufo, and . Velastin, On the efficacy of texture analysis for crowd monitoring, SIB-GRAPI, 1998.

D. Onoro, -. Rubio, and R. , Towards perspective-free object counting with deep learning, ECCV, 2008.

N. Paragios and V. Ramesh, A mrf-based approach for real-time subway monitoring, CVPR, 2001.

V. Rabaud and S. Belongie, Counting crowded moving objects, CVPR, vol.1, 2006.

H. Viresh-ranjan, M. Le, and . Hoai, Iterative crowd counting. ECCV, 2008.

S. Carlo, A. Regazzoni, and . Tesei, Distributed data fusion for real-time crowding estimation, Signal Processing, vol.53, issue.1, pp.47-63, 1996.

D. Ryan, S. Denman, C. Fookes, and S. Sridharan, Crowd counting using multiple local features, DICTA, vol.1, 2009.

S. Deepak-babu-sam, R. Surya, and . Babu, Switching convolutional neural network for crowd counting, CVPR, 2008.

Z. Shen, Y. Xu, B. Ni, M. Wang, J. Hu et al., Crowd counting via adversarial cross-scale consistency pursuit, CVPR, vol.2, p.7, 2018.

Z. Shi, L. Zhang, Y. Liu, X. Cao, Y. Ye et al., Crowd counting with deep negative correlation learning, CVPR, 2018.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, ICLR, vol.4, p.7, 2015.

A. Vishwanath, . Sindagi, M. Vishal, and . Patel, Cnn-based cascaded multi-task learning of high-level prior and density estimation for crowd counting, AVSS, issue.2, 2017.

A. Vishwanath, . Sindagi, M. Vishal, and . Patel, Generating highquality crowd density maps using contextual pyramid cnns, ICCV, vol.7, 2003.

R. Stewart, M. Andriluka, and A. Ng, End-to-end people detection in crowded scenes, CVPR, 2016.

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, CVPR, 2001.

P. Viola, J. Michael, D. Jones, and . Snow, Detecting pedestrians using patterns of motion and appearance, IJCV, vol.63, issue.2, pp.153-161, 2003.

E. Walach and L. Wolf, Learning to count with cnn boosting, ECCV, 2016.

C. Wang, H. Zhang, L. Yang, S. Liu, and X. Cao, Deep people counting in extremely dense crowds, ACM MM, 2015.

M. Wang and X. Wang, Automatic adaptation of a generic pedestrian detector to a specific traffic scene, CVPR, 2011.

Z. Wang, A. C. Bovik, R. Hamid, E. Sheikh, and . Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE transactions on image processing, vol.13, issue.4, pp.600-612, 2004.

B. Wu and R. Nevatia, Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors, ICCV, vol.1, 2005.

F. Xiong, X. Shi, and D. Yeung, Spatiotemporal modeling for crowd counting in videos, ICCV, vol.2, 2017.

C. Zhang, H. Li, X. Wang, and X. Yang, Cross-scene crowd counting via deep convolutional neural networks, CVPR, vol.7, 2006.

Y. Zhang, D. Zhou, S. Chen, S. Gao, and Y. Ma, Single-image crowd counting via multi-column convolutional neural network, CVPR, vol.7, 2006.

Z. Zhao, H. Li, R. Zhao, and X. Wang, Crossing-line crowd counting with two-phase deep neural networks, In ECCV, issue.2, 2016.