Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting

28 August 2019

Papers citing "Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting"

9 / 59 papers shown

Title
Understanding the impact of mistakes on background regions in crowd counting Davide Modolo Bing Shuai Rahul Rama Varior Joseph Tighe 28 17 0 30 Mar 2020
CNN-based Density Estimation and Crowd Counting: A Survey Guangshuai Gao Junyu Gao Qingjie Liu Qi. Wang Yunhong Wang 22 154 0 28 Mar 2020
Efficient Crowd Counting via Structured Knowledge Transfer Lingbo Liu Jiaqi Chen Hefeng Wu Tianshui Chen Guanbin Li Liang Lin 29 64 0 23 Mar 2020
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting Pongpisit Thanasutives Ken-ichi Fukui M. Numao B. Kijsirikul 30 63 0 12 Mar 2020
AutoScale: Learning to Scale for Crowd Counting and Localization Chenfeng Xu Dingkang Liang Yongchao Xu S. Bai Wei Zhan X. Bai Masayoshi Tomizuka 27 105 0 20 Dec 2019
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance Junyu Gao Yuan. Yuan Qi. Wang 13 13 0 08 Dec 2019
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting Weizhe Liu Mathieu Salzmann Pascal Fua AAML 27 9 0 26 Nov 2019
Estimating People Flows to Better Count Them in Crowded Scenes Weizhe Liu Mathieu Salzmann Pascal Fua OT 3DH 27 38 0 25 Nov 2019
Crowd Counting via Segmentation Guided Attention Networks and Curriculum Loss Qian Wang T. Breckon 3DPC 26 6 0 18 Nov 2019