Crowd counting with crowd attention convolutional neural network
暂无分享,去创建一个
Jiwei Chen | Zengfu Wang | Wen Su | Zengfu Wang | Jiwei Chen | Wen Su
[1] Bingbing Ni,et al. Crowd Counting via Adversarial Cross-Scale Consistency Pursuit , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[2] Sergio A. Velastin,et al. Crowd analysis: a survey , 2008, Machine Vision and Applications.
[3] Vishal M. Patel,et al. CNN-Based cascaded multi-task learning of high-level prior and density estimation for crowd counting , 2017, 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
[4] Vladlen Koltun,et al. Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.
[5] Guoyan Zheng,et al. Crowd Counting with Deep Negative Correlation Learning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[6] Shenghua Gao,et al. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] Shiv Surya,et al. Switching Convolutional Neural Network for Crowd Counting , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Yang Wang,et al. Crowd Counting Using Scale-Aware Attention Networks , 2019, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).
[9] Shuicheng Yan,et al. An HOG-LBP human detector with partial occlusion handling , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[10] Nuno Vasconcelos,et al. Bayesian Poisson regression for crowd counting , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[11] Bingbing Ni,et al. Crowded Scene Analysis: A Survey , 2015, IEEE Transactions on Circuits and Systems for Video Technology.
[12] Xiaogang Wang,et al. Cross-scene crowd counting via deep convolutional neural networks , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] A. Marana,et al. On the efficacy of texture analysis for crowd monitoring , 1998, Proceedings SIBGRAPI'98. International Symposium on Computer Graphics, Image Processing, and Vision (Cat. No.98EX237).
[14] Wei Lin,et al. Learning From Synthetic Data for Crowd Counting in the Wild , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Qiang Chen,et al. Network In Network , 2013, ICLR.
[16] 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.
[17] Nuno Vasconcelos,et al. Privacy preserving crowd monitoring: Counting people without people models or tracking , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Meng Wang,et al. pDisVPL: Probabilistic Discriminative Visual Part Learning for Image Classification , 2018, IEEE MultiMedia.
[19] R. Venkatesh Babu,et al. Top-Down Feedback for Crowd Counting Convolutional Neural Network , 2018, AAAI.
[20] Haroon Idrees,et al. Multi-source Multi-scale Counting in Extremely Dense Crowd Images , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[21] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] R. Venkatesh Babu,et al. Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[24] Deyu Meng,et al. DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[25] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[26] Larry S. Davis,et al. Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Ivan Laptev,et al. Density-aware person detection and tracking in crowds , 2011, ICCV.
[28] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[29] Srinivas S. Kruthiventi,et al. CrowdNet: A Deep Convolutional Network for Dense Crowd Counting , 2016, ACM Multimedia.
[30] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[31] Wensheng Zhang,et al. Large-Scale Online Multitask Learning and Decision Making for Flexible Manufacturing , 2016, IEEE Transactions on Industrial Informatics.
[32] Baoqun Yin,et al. Removing background interference for crowd counting via de-background detail convolutional network , 2019, Neurocomputing.
[33] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Faliang Chang,et al. Multi-resolution attention convolutional neural network for crowd counting , 2019, Neurocomputing.
[35] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[36] Yan Wang,et al. Dense crowd counting from still images with convolutional neural networks , 2016, J. Vis. Commun. Image Represent..
[37] 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).
[38] Dit-Yan Yeung,et al. Spatiotemporal Modeling for Crowd Counting in Videos , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[39] Sridha Sridharan,et al. Crowd Counting Using Multiple Local Features , 2009, 2009 Digital Image Computing: Techniques and Applications.
[40] Vishal M. Patel,et al. A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density Estimation , 2017, Pattern Recognit. Lett..
[41] Nan Wang,et al. Counting challenging crowds robustly using a multi-column multi-task convolutional neural network , 2018, Signal Process. Image Commun..
[42] Tieniu Tan,et al. Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection , 2008, 2008 19th International Conference on Pattern Recognition.
[43] Vishal M. Patel,et al. Generating High-Quality Crowd Density Maps Using Contextual Pyramid CNNs , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[44] Huadong Ma,et al. Robust Head-Shoulder Detection by PCA-Based Multilevel HOG-LBP Detector for People Counting , 2010, 2010 20th International Conference on Pattern Recognition.