Rethinking Spatial Invariance of Convolutional Networks for Object Counting-Reference-Cited by-同舟云学术

Rethinking Spatial Invariance of Convolutional Networks for Object Counting

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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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

Link

Reference82 articles.

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

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