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What Can Help Pedestrian Detection? (CVPR2017) #532

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hurutoriya opened this Issue Nov 30, 2017 · 0 comments

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@hurutoriya
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hurutoriya commented Nov 30, 2017

一言でいうと

HyperLearnerと呼ばれるCNNで得られた複数の特徴量(オプティカルフロー、深度特徴、物体検出、etc.)を統合して歩行者検出でSOTAを達成。Baselineの手法と比較しても速度の低下も防げている。

論文リンク

http://openaccess.thecvf.com/content_cvpr_2017/papers/Mao_What_Can_Help_CVPR_2017_paper.pdf

著者/所属機関

Jiayuan Mao∗†
The Institute for Theoretical Computer Science (ITCS)
Institute for Interdisciplinary Information Sciences
Tsinghua University, Beijing, China

Tete Xiao∗†
School of Electronics Engineering and Computer Science
Peking University, Beijing, China

投稿日付(yyyy/MM/dd)

概要

image

Baselineとの比較

新規性・差分

手法

結果

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