Detection of human body parts on the image using the neural networks and the attention model

V. Sorokina, S. Ablameyko
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引用次数: 1

Abstract

Human body parts detection is a challenging task, which has a lot of applications. In this paper, we propose an algorithm to detect human body parts on images using the OpenPose neural network and the attention model. The novelty of the proposed algorithm is that it is based on a convolutional neural network that uses non-parametric representation to associate the body parts with people in an image in combination with the attention model that learns to focus on specific regions of the input image. The algorithm is part of the Smart Cropping system developed by the authors with the aim to cut necessary pieces of clothing in images and prepare e-commerce catalogues.
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利用神经网络和注意力模型检测图像上的人体部位
人体部位检测是一项具有挑战性的任务,有很多应用。在本文中,我们提出了一种使用OpenPose神经网络和注意力模型在图像上检测人体部位的算法。所提出的算法的新颖性在于,它基于卷积神经网络,该网络使用非参数表示将身体部位与图像中的人相关联,并结合学习关注输入图像的特定区域的注意力模型。该算法是作者开发的智能裁剪系统的一部分,目的是在图像中裁剪必要的衣服,并准备电子商务目录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
0.50
自引率
0.00%
发文量
21
审稿时长
16 weeks
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