Learning a perspective-embedded deconvolution network for crowd counting
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]
|Collections||ANU Research Publications|
|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|
|01_Zhao_Learning_a_2017.pdf||378.76 kB||Adobe PDF||Request a copy|
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