electronics Article Automatic Detection of Discrimination Actions from Social Images Zhihao Wu 1 , Baopeng Zhang 1,*, Tianchen Zhou 1, Yan Li 1 and Jianping Fan 2 1 School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
[email protected] (Z.W.);
[email protected] (T.Z.);
[email protected] (Y.L.) 2 AI Lab, Lenovo Research, Beijing 100094, China;
[email protected] * Correspondence:
[email protected] Abstract: In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co- operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches. Keywords: discrimination action recognition; relationship prediction; representation learning Citation: Wu, Z.; Zhang, B.; Zhou, T.; 1. Introduction Li, Y.; Fan, J. Automatic Detection of In line with the popularity of smart devices, most social platforms, such as Facebook Discrimination Actions from Social and Twitter, have incorporated image sharing into their important functions.