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A Multi-view Deep Learning Approach for Detecting Threats on 3D Human Body

机译:一种检测3D人体威胁的多视图深度学习方法

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Deep Neural Network-based methods have recently shown an outstanding performance on object detection tasks in 2D scenarios. But many tasks in real world requires object detection in 3D space. In order to narrow this gap, we investigate the task of detection and localization in 3D human body in this paper, and propose a multi-view-based deep learning approach to solve this issue. The experiments show that the proposed approach can effectively detect and locate specific stuff in 3D human body with high accuracy.
机译:最近,基于深度神经网络的方法在2D方案中最近对对象检测任务的出色表现出色。但是,现实世界中的许多任务需要在3D空间中检测到的对象检测。为了缩小这种差距,我们在本文中调查了3D人体中检测和定位的任务,并提出了一种基于多视图的深度学习方法来解决这个问题。实验表明,该方法可以高精度地有效地检测和定位3D人体中的特定东西。

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