Rethinking Spatial Invariance of Convolutional Networks for Object Counting

Author:

Cheng Zhi-Qi1,Dai Qi2,Li Hong3,Song Jingkuan4,Wu Xiao3,Hauptmann Alexander G.1

Affiliation:

1. Carnegie Mellon University

2. Microsoft Research Asia

3. Southwest Jiaotong University

4. University of Electronic Science and Technology of China

Funder

Air Force Research Laboratory

U.S. Department of Commerce

National Institute of Standards and Technology (NIST)

Intelligence Advanced Research Projects Activity (IARPA)

Defense Advanced Research Projects Agency (DARPA)

Publisher

IEEE

Reference82 articles.

1. Attentional Neural Fields for Crowd Counting

2. Relational Attention Network for Crowd Counting

3. Embedding perspective analysis into multi-column convolutional neural network for crowd counting;yang;IEEE TIP,2020

4. Crowd counting via perspective-guided fractional-dilation convolution;yan;IEEE TMM,2021

5. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network

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