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Learning a perspective-embedded deconvolution network for crowd counting

Zhao, Muming; Zhang, Jian; Porikli, Fatih; Zhang, Chongyang; Zhang, Wenjun

Description

We present a novel deep learning framework for crowd counting by learning a perspective-embedded deconvolution network. Perspective is an inherent property of most surveillance scenes. Unlike the traditional approaches that exploit the perspective as a separate normalization, we propose to fuse the perspective into a deconvolution network, aiming to obtain a robust, accurate and consistent crowd density map. Through layer-wise fusion, we merge perspective maps at different resolutions into...[Show more]

CollectionsANU Research Publications
Date published: 2017
Type: Conference paper
URI: http://hdl.handle.net/1885/210129
Source: Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2017
Book Title: 2017 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2017
DOI: 10.1109/ICME.2017.8019501

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