基于目标的图像判别关系识别

Yan Li, Baopeng Zhang, Jiajie Tian, Rui Li, Sibo Wang, Jianping Fan
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引用次数: 0

摘要

随着自媒体的发展,我们可以在互联网上自由发布图片,或多或少会出现一些歧视性的图片。歧视是一种情感关系。然而,目前还没有开放的数据集来帮助我们完成歧视图像检测的任务。在本文中,我们创建了一个简单的数据集,可用于检测歧视性关系。然后,在这个数据集上,我们提出了一个歧视性关系检测的基线。该基线是一个基于翻译嵌入模型的多任务网络,既可以输出图中对象的动作类别,也可以输出两者之间的关系类别。实验表明,我们的多任务网络可以有效地检测出关系,并且优于简单的翻译嵌入模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object-based Image Discrimination Relationship Recognition
With the development of self-media, we can publish images freely on the Internet, and there will be some discriminatory images more or less. Discrimination is an emotional relationship. However, there is no open data set to help us complete the task of discriminatory image detection. In this article, we created a simple data set that can be used to detect discriminatory relationships. Then, on this data set, we propose a baseline for discriminatory relationship detection. This baseline is a multi-task network based on translation embedding model, which can output both the action categories of objects in the graph and the relationship categories between the two. Experiments show that our multi-task network can effectively detect relationships, and it is better than the simple translation embedding model.
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