BriefGPT.xyz
Jul, 2019
人体姿态估计在现实世界拥挤场景中的应用
Human Pose Estimation for Real-World Crowded Scenarios
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Thomas Golda, Tobias Kalb, Arne Schumann, Jürgen Beyerer
TL;DR
本论文针对人群姿态估计的问题,提出了通过数据增强方法、显式识别遮挡的身体部位和使用合成数据集来优化姿态估计。论文的实验结果表明这些方法提高了模型的准确性,使其在人群场景下获得了与当前最先进方法相媲美的结果。
Abstract
human pose estimation
has recently made significant progress with the adoption of
deep convolutional neural networks
. Its many applications have attracted tremendous interest in recent years. However, many practi
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