Pedestrian Gender Detection Based on Mask R-CNN

Xinyue Li, Samuel Cheng
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引用次数: 3

Abstract

Based on Mask R-CNN, one of the most significant models for instance segmentation, we present our pedestrian gender detection algorithm in this paper. First of all, we verify the effectiveness of Mask R-CNN in pedestrian detection. On this basis, we design our network by merging Mask R-CNN with a gender recognition branch. And due to the lack of current datasets, we not only present a method to train our model, but also build a shopping mall dataset to test our model. The application of our detection model to our small dataset is of great significance to the business planning and the security maintenance of the entertainment center.
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基于掩模R-CNN的行人性别检测
本文基于实例分割中最重要的模型之一Mask R-CNN,提出了一种行人性别检测算法。首先,我们验证了Mask R-CNN在行人检测中的有效性。在此基础上,我们通过将Mask R-CNN与性别识别分支合并来设计网络。由于缺乏现有的数据集,我们不仅提出了一种方法来训练我们的模型,而且建立了一个购物中心数据集来测试我们的模型。将我们的检测模型应用到我们的小数据集上,对于娱乐中心的业务规划和安全维护具有重要意义。
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