·1080· 智能系统学报 第16卷 28th International Conference on Neural Information 7552 Processing Systems.Montreal,Canada,2015: [23]HAN Xintong,WU Zuxuan,HUANG Weilin,et al. 2017-2025. Compatible and diverse fashion image inpainting [15]SZEGEDY C,LIU Wei,JIA Yangqing,et al.Going [EB/oL.(2019-04-24)[2020-12-01]https:/axiv.org deeper with convolutions[C]//Proceedings of the IEEE abs/1902.01096. Conference on Computer Vision and Pattern Recogni- [24]PANDEY N,SAVAKIS A.Poly-GAN:multi-condi- tion.Boston,USA,2015:1-9. tioned GAN for fashion synthesis[J].Neurocomputing, [16]周飞燕，金林鹏，董军.卷积神经网络研究综述.计 2020,414:356-364 算机学报，2017,40(6：1229-1251. [25]DONG Haoye,LIANG Xiaodan,SHEN Xiaohui,et al. ZHOU Feiyan,JIN Linpeng,DONG Jun.Review of convolutional neural network[J].Chinese journal of Towards multi-pose guided virtual try-on network computers,.2017,40(6):1229-1251. [Cl/Proceedings of the IEEE/CVF International Confer- [17]DUTA IC,LIU L,ZHU F,et al.Pyramidal convolutio- ence on Computer Vision.Seoul,Korea(South),2019: n:rethinking convolutional neural networks for vis-ual 9025-9034 recognition[EB/0L].(2020-06-20)[2020-12-011 作者简介： https://arxiv.org/abs/2006.11538. 姜义，讲师，主要研究方向为人工 [18]ARJOVSKY M,BOTTOU L.Towards principled meth- 智能、传感器网络、分布式系统。 ods for training generative adversarial networks [EB/OL].(2017-01-17)[2020-12-01]https:/axiv.org/ abs/1701.04862 [19]MIYATO T,KATAOKA T,KOYAMA M,et al.Spec- tral normalization for generative adversarial networks [C]//6th International Conference on Learning Repres- 吕荣镇，硕士研究生，主要研究方 entations.Vancouver,Canada,2018. 向为人工智能。 [20]WANG Z.WANG G.HUANG B,et al.Masked face re- cognition dataset and application[EB/OL].(2020-03- 23)2020-12-011 https:/arxiv.org/abs/2003.09093. [21]LIU Ziwei,LUO Ping,WANG Xiaogang,et al.Deep learning face attributes in the wild[C]//Proceedings of the IEEE International Conference on Computer Vision. 刘明珠，副教授，主要研究方向为 通信与信息系统。发表学术论文10 Santiago,Chile,2015:3730-3738. 余篇。 [22]HAN Xintong,WU Zuxuan,WU Zhe,et al.VITON:an image-based virtual try-on network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pat- tern Recognition.Salt Lake City,USA,2018:7543-28th International Conference on Neural Information Processing Systems. Montreal, Canada, 2015: 2017−2025. SZEGEDY C, LIU Wei, JIA Yangqing, et al. Going deeper with convolutions[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recogni￾tion. Boston, USA, 2015: 1−9. [15] 周飞燕, 金林鹏, 董军. 卷积神经网络研究综述 [J]. 计 算机学报, 2017, 40(6): 1229–1251. ZHOU Feiyan, JIN Linpeng, DONG Jun. Review of convolutional neural network[J]. Chinese journal of computers, 2017, 40(6): 1229–1251. [16] DUTA I C, LIU L, ZHU F, et al. Pyramidal convolutio￾n: rethinking convolutional neural networks for vis-ual recognition[EB/OL].(2020-06-20)[2020-12-01] https://arxiv.org/abs/2006.11538. [17] ARJOVSKY M, BOTTOU L. Towards principled meth￾ods for training generative adversarial networks [EB/OL]. (2017-01-17)[2020-12-01] https://arxiv.org/ abs/1701.04862. [18] MIYATO T, KATAOKA T, KOYAMA M, et al. Spec￾tral normalization for generative adversarial networks [C]//6th International Conference on Learning Repres￾entations. Vancouver, Canada, 2018. [19] WANG Z, WANG G, HUANG B, et al. Masked face re￾cognition dataset and application[EB/OL].(2020-03- 23)[2020-12-01] https://arxiv.org/abs/2003.09093. [20] LIU Ziwei, LUO Ping, WANG Xiaogang, et al. Deep learning face attributes in the wild[C]//Proceedings of the IEEE International Conference on Computer Vision. Santiago, Chile, 2015: 3730−3738. [21] HAN Xintong, WU Zuxuan, WU Zhe, et al. VITON: an image-based virtual try-on network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pat￾tern Recognition. Salt Lake City, USA, 2018: 7543− [22] 7552. HAN Xintong, WU Zuxuan, HUANG Weilin, et al. Compatible and diverse fashion image inpainting [EB/OL]. (2019-04-24)[2020-12-01] https://arxiv.org/ abs/1902.01096. [23] PANDEY N, SAVAKIS A. Poly-GAN: multi-condi￾tioned GAN for fashion synthesis[J]. Neurocomputing, 2020, 414: 356–364. [24] DONG Haoye, LIANG Xiaodan, SHEN Xiaohui, et al. Towards multi-pose guided virtual try-on network [C]//Proceedings of the IEEE/CVF International Confer￾ence on Computer Vision. Seoul, Korea (South), 2019: 9025−9034. [25] 作者简介： 姜义，讲师，主要研究方向为人工 智能、传感器网络、分布式系统。 吕荣镇，硕士研究生，主要研究方 向为人工智能。 刘明珠，副教授，主要研究方向为 通信与信息系统。发表学术论文 10 余篇。 ·1080· 智 能 系 统 学 报 第 16 卷