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Crowd Counting via Hierarchical Scale Recalibration Network

Crowd Counting via Hierarchical Scale Recalibration Network

European Conference on Artificial Intelligence (ECAI), 2020
7 March 2020
Zhikang Zou
Yifan Liu
Shuangjie Xu
Wei Wei
S. Wen
Pan Zhou
ArXiv (abs)PDFHTML

Papers citing "Crowd Counting via Hierarchical Scale Recalibration Network"

25 / 25 papers shown
Spatiotemporal Dilated Convolution with Uncertain Matching for
  Video-based Crowd Estimation
Spatiotemporal Dilated Convolution with Uncertain Matching for Video-based Crowd EstimationIEEE transactions on multimedia (IEEE Trans. Multimedia), 2021
Yu-Jen Ma
Hong-Han Shuai
Wen-Huang Cheng
286
56
0
29 Jan 2021
Scale-Aware Network with Regional and Semantic Attentions for Crowd
  Counting under Cluttered Background
Scale-Aware Network with Regional and Semantic Attentions for Crowd Counting under Cluttered Background
Qiaosi Yi
Yunxin Liu
Aiwen Jiang
Juncheng Li
Kangfu Mei
Mingwen Wang
218
8
0
05 Jan 2021
A Survey on Deep Learning-based Single Image Crowd Counting: Network
  Design, Loss Function and Supervisory Signal
A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory SignalNeurocomputing (Neurocomputing), 2020
Haoyue Bai
Jiageng Mao
Shueng-Han Gary Chan
434
29
0
31 Dec 2020
Analyzing Worldwide Social Distancing through Large-Scale Computer
  Vision
Analyzing Worldwide Social Distancing through Large-Scale Computer Vision
Isha Ghodgaonkar
S. Chakraborty
Vishnu Banna
Shane Allcroft
M. Metwaly
...
Mark Daniel Ward
Wei Zakharov
D. Ebert
D. Barbarash
George K. Thiruvathukal
229
28
0
27 Aug 2020
Improving the Learning of Multi-column Convolutional Neural Network for
  Crowd Counting
Improving the Learning of Multi-column Convolutional Neural Network for Crowd CountingACM Multimedia (ACM MM), 2019
Zhi-Qi Cheng
Jun-Xiu Li
Jingdong Sun
Xiao-Jun Wu
Jun-Yan He
Alexander G. Hauptmann
SSL
172
94
0
17 Sep 2019
Crowd Counting on Images with Scale Variation and Isolated Clusters
Crowd Counting on Images with Scale Variation and Isolated Clusters
Haoyue Bai
Song Wen
Shueng-Han Gary Chan
152
28
0
09 Sep 2019
Enhanced 3D convolutional networks for crowd counting
Enhanced 3D convolutional networks for crowd countingBritish Machine Vision Conference (BMVC), 2019
Zhikang Zou
Huiliang Shao
Xiaoye Qu
Wei Wei
Pan Zhou
182
40
0
12 Aug 2019
Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs
Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs
Zhikang Zou
Yu Cheng
Xiaoye Qu
S. Ji
Xiaoxiao Guo
Pan Zhou
265
52
0
07 Aug 2019
Learning from Synthetic Data for Crowd Counting in the Wild
Learning from Synthetic Data for Crowd Counting in the Wild
Qi. Wang
Junyu Gao
Wei Lin
Yuan. Yuan
328
586
0
08 Mar 2019
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network
Crowd Counting and Density Estimation by Trellis Encoder-Decoder NetworkComputer Vision and Pattern Recognition (CVPR), 2019
Xiaolong Jiang
Zehao Xiao
Baochang Zhang
Xiantong Zhen
Xianbin Cao
David Doermann
Ling Shao
3DV
196
346
0
03 Mar 2019
Divide and Grow: Capturing Huge Diversity in Crowd Images with
  Incrementally Growing CNN
Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNN
Deepak Babu Sam
Neeraj N. Sajjan
R. Venkatesh Babu
182
227
0
26 Jul 2018
CBAM: Convolutional Block Attention Module
CBAM: Convolutional Block Attention ModuleEuropean Conference on Computer Vision (ECCV), 2018
Sanghyun Woo
Jongchan Park
Joon-Young Lee
In So Kweon
746
22,529
0
17 Jul 2018
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid
Di Kang
Antoni B. Chan
123
114
0
16 May 2018
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
Xialei Liu
Joost van de Weijer
Andrew D. Bagdanov
SSL
228
303
0
08 Mar 2018
CSRNet: Dilated Convolutional Neural Networks for Understanding the
  Highly Congested Scenes
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Yuhong Li
Xiaofan Zhang
Deming Chen
620
1,554
0
27 Feb 2018
Crowd counting via scale-adaptive convolutional neural network
Crowd counting via scale-adaptive convolutional neural network
Jun Liu
Miaojing Shi
Qiaobo Chen
319
260
0
13 Nov 2017
Squeeze-and-Excitation Networks
Squeeze-and-Excitation Networks
Jie Hu
Li Shen
Samuel Albanie
Gang Sun
Enhua Wu
4.4K
33,171
0
05 Sep 2017
Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs
Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs
Vishwanath A. Sindagi
Vishal M. Patel
331
662
0
02 Aug 2017
Switching Convolutional Neural Network for Crowd Counting
Switching Convolutional Neural Network for Crowd Counting
Deepak Babu Sam
Shiv Surya
R. Venkatesh Babu
374
953
0
01 Aug 2017
CNN-based Cascaded Multi-task Learning of High-level Prior and Density
  Estimation for Crowd Counting
CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting
Vishwanath A. Sindagi
Vishal M. Patel
271
532
0
30 Jul 2017
FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in
  City Cameras
FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras
Shanghang Zhang
Guanhang Wu
João Paulo Costeira
José M. F. Moura
AI4TS
261
216
0
29 Jul 2017
Spatiotemporal Modeling for Crowd Counting in Videos
Spatiotemporal Modeling for Crowd Counting in Videos
Feng Xiong
Xingjian Shi
Dit-Yan Yeung
170
190
0
25 Jul 2017
Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks -
  Counting, Detection, and Tracking
Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking
Di Kang
Zheng Ma
Antoni B. Chan
247
190
0
29 May 2017
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic OptimizationInternational Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
5.0K
164,280
0
22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image RecognitionInternational Conference on Learning Representations (ICLR), 2014
Karen Simonyan
Andrew Zisserman
FAttMDE
4.0K
110,317
0
04 Sep 2014
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