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We propose an attention-injective deformable convolutional network called ADCrowdNet for crowd understanding that can address the accuracy degradation problem of highly congested noisy scenes.
Robust real-time face detection
Paul Viola and Michael J Jones · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Histograms of oriented gradients for human detection
Navneet Dalal and Bill Triggs · 2005
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Privacy preserving crowd monitoring: Counting people without people models or tracking
Antoni B Chan, Zhang-Sheng John Liang, and Nuno Vasconcelos · 2008
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Learning to count objects in images
Victor Lempitsky and Andrew Zisserman · 2010
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Feature mining for localised crowd counting
Ke Chen, Chen Change Loy, Shaogang Gong, and Tony Xiang · 2012
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Pedestrian detection: An evaluation of the state of the art
Piotr Dollár, Christian Wojek, Bernt Schiele, and Pietro Perona · 2012
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Cumulative attribute space for age and crowd density estimation
Ke Chen, Shaogang Gong, Tao Xiang, and Chen Change Loy · 2013
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Multi-source multi-scale counting in extremely dense crowd images
Haroon Idrees, Imran Saleemi, Cody Seibert, and Mubarak Shah · 2013
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Extremely overlapping vehicle counting
Ricardo Guerrero-Gómez-Olmedo, Beatriz Torre-Jiménez, Roberto López-Sastre, Saturnino Maldonado-Bascón, and Daniel Onoro-Rubio · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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Count forest: Co-voting uncertain number of targets using random forest for crowd density estimation
Viet-Quoc Pham, Tatsuo Kozakaya, Osamu Yamaguchi, and Ryuzo Okada · 2015
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Cross-scene crowd counting via deep convolutional neural networks
Cong Zhang, Hongsheng Li, Xiaogang Wang, and Xiaokang Yang · 2015
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Crowdnet: A deep convolutional network for dense crowd counting
Lokesh Boominathan, Srinivas S.S. Kruthiventi, and R. Venkatesh Babu · 2016
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Fully convolutional crowd counting on highly congested scenes
Mark Marsden, Kevin McGuinness, Suzanne Little, and Noel E O’Connor · 2016
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Towards perspective-free object counting with deep learning
Daniel Onoro-Rubio and Roberto J López-Sastre · 2016
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Generating high-quality crowd density maps using contextual pyramid cnns
Vishwanath A Sindagi and Vishal M Patel · 2017
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Fcn-rlstm: Deep spatio-temporal neural networks for vehicle counting in city cameras
Shanghang Zhang, Guanhang Wu, Joao P Costeira, and José MF Moura · 2017
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Scale aggregation network for accurate and efficient crowd counting
Xinkun Cao, Zhipeng Wang, Yanyun Zhao, and Fei Su · 2018
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Multi-context attention for human pose estimation
Xiao Chu, Wei Yang, Wanli Ouyang, Cheng Ma, Alan L Yuille, and Xiaogang Wang · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Crowd counting by adaptively fusing predictions from an image pyramid
Di Kang and Antoni B. Chan · 2018
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Chong Shang, Bo, Haizhou Ai, and Bai · 2016
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Learning to count with cnn boosting
Elad Walach and Lior Wolf · 2016
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Single-image crowd counting via multi-column convolutional neural network
Yingying Zhang, Desen Zhou, Siqin Chen, Shenghua Gao, and Yi Ma · 2016
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Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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End-to-end instance segmentation with recurrent attention
Mengye Ren and Richard S Zemel · 2017
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Switching convolutional neural network for crowd counting
Deepak Babu Sam, Shiv Surya, and R Venkatesh Babu · 2017
Cited alongside, same era.
Structured inhomogeneous density map learning for crowd counting
Hanhui Li, Xiangjian He, Hefeng Wu, Saeed Amirgholipour Kasmani, Ruomei Wang, Xiaonan Luo, and Liang Lin · 2018
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CSRNet: Dilated convolutional neural networks for understanding the highly congested scenes
Yuhong Li, Xiaofan Zhang, and Deming Chen · 2018
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Crowd counting using deep recurrent spatial-aware network
Lingbo Liu, Hongjun Wang, Guanbin Li, Wanli Ouyang, and Liang Lin · 2018
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Attentive generative adversarial network for raindrop removal from a single image
Rui Qian, Robby T Tan, Wenhan Yang, Jiajun Su, and Jiaying Liu · 2018
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Revisiting dilated convolution: A simple approach for weakly-and semi-supervised semantic segmentation
Yunchao Wei, Huaxin Xiao, Honghui Shi, Zequn Jie, Jiashi Feng, and Thomas S Huang · 2018
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Crowd counting via multi-view scale aggregation networks
Zhilin Qiu, Lingbo Liu, Guanbin Li, Qing Wang, Nong Xiao, and Liang Lin · 2019
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