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作 者:林豪发 罗艳玲 卢娜 胡定兴 朱大琴 LIN Haofa;LUO Yanling;LU Na;HU Dingxing;ZHU Daqin(School of Artificial Intelligence,Wuhan Technology and Business University,Wuhan 430065,China;Institute of Information and Intelligent Engineering Applications,Wuhan 430065,China;Academic Affairs Division,Wuhan University of Science and Technology,Wuhan 430081,China)
机构地区:[1]武汉工商学院人工智能学院,湖北武汉430065 [2]信息与智能工程应用研究所,湖北武汉430065 [3]武汉科技大学教务部,湖北武汉430081
出 处:《现代信息科技》2025年第8期61-64,70,共5页Modern Information Technology
基 金:武汉工商学院校级基金项目(A2023017)。
摘 要:服装草图的图像转换在视觉编辑、服装设计和人机交互等领域有着巨大的应用价值。目前草图转换的对象,大多数都是比较简单的图形,比如人脸、人体姿态、动物姿态、鞋子和包包。基于草图转换的工作由于难以处理复杂纹理结构的图像,因此难以解决服装草图的图像转换任务。为了解决这个问题,在上述工作的基础上提出了草图到服装图像转换的应用研究。通过U~2-Net网络模型逆向生成的服装仿真草图,完成对服装草图数据集的构建,然后利用改进后的BicycleGAN网络对其进行训练,以实现草图转换,最后对比了改进前后的实验效果。实验结果表明,改进后的BicycleGAN网络模型比改进前有了较大的提升,能够更有效地完成服装草图到真实服装图像的转换任务。The image conversion of clothing sketches has enormous application value in fields such as visual editing,clothing design,and human-computer interaction.At present,most of the objects converted from sketches are relatively simple shapes,such as faces,human postures,animal postures,shoes,and bags.The work based on sketch conversion is difficult to handle images with complex texture structures,making it challenging to solve the task of image conversion for clothing sketches.To solve this problem,an application research on sketch to clothing image conversion is proposed based on the above work.Through the reverse generation of clothing simulation sketches using the U2-Net network model,the construction of the clothing sketch dataset is completed.Then,the improved BicycleGAN network is used for training to achieve sketch conversion.Finally,the experimental effects before and after the improvement are compared.The experiment shows that the improved BicycleGAN network model has significant improvement compared to before,and with the improved network proposed in this paper,the task of converting clothing sketches to real clothing images can be effectively completed.
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