The objective of style transfer is to maintain the content of an image while transferring the style of another image.However,conventional methods face challenges in preserving facial features,especially in Korean port...The objective of style transfer is to maintain the content of an image while transferring the style of another image.However,conventional methods face challenges in preserving facial features,especially in Korean portraits where elements like the“Gat”(a traditional Korean hat)are prevalent.This paper proposes a deep learning network designed to perform style transfer that includes the“Gat”while preserving the identity of the face.Unlike traditional style transfer techniques,the proposed method aims to preserve the texture,attire,and the“Gat”in the style image by employing image sharpening and face landmark,with the GAN.The color,texture,and intensity were extracted differently based on the characteristics of each block and layer of the pre-trained VGG-16,and only the necessary elements during training were preserved using a facial landmark mask.The head area was presented using the eyebrow area to transfer the“Gat”.Furthermore,the identity of the face was retained,and style correlation was considered based on the Gram matrix.To evaluate performance,we introduced a metric using PSNR and SSIM,with an emphasis on median values through new weightings for style transfer in Korean portraits.Additionally,we have conducted a survey that evaluated the content,style,and naturalness of the transferred results,and based on the assessment,we can confidently conclude that our method to maintain the integrity of content surpasses the previous research.Our approach,enriched by landmarks preservation and diverse loss functions,including those related to“Gat”,outperformed previous researches in facial identity preservation.展开更多
该文针对第二代居民身份证制证用数字相片智能检测问题进行研究并简述主要的实现技术。文章分析An il K.Ja in等提出的光线补偿方法的不足和YCbC r颜色空间在应用中的优点。一种基于环境采样卡的图像校正方法和YCbC r颜色空间上经过非...该文针对第二代居民身份证制证用数字相片智能检测问题进行研究并简述主要的实现技术。文章分析An il K.Ja in等提出的光线补偿方法的不足和YCbC r颜色空间在应用中的优点。一种基于环境采样卡的图像校正方法和YCbC r颜色空间上经过非线性分段色彩变换到YCb C r空间的肤色模型。该文介绍了作者在肤色模型基础上眼睛标定的具体实现技术,提出一种基于像素统计的“密度”滤波处理方法来提高肤色判断的鲁棒性。介绍了优先眼睛标定的其它数字相片规格指标的综合智能检测实现技术。展开更多
基金supported by Metaverse Lab Program funded by the Ministry of Science and ICT(MSIT),and the Korea Radio Promotion Association(RAPA).
文摘The objective of style transfer is to maintain the content of an image while transferring the style of another image.However,conventional methods face challenges in preserving facial features,especially in Korean portraits where elements like the“Gat”(a traditional Korean hat)are prevalent.This paper proposes a deep learning network designed to perform style transfer that includes the“Gat”while preserving the identity of the face.Unlike traditional style transfer techniques,the proposed method aims to preserve the texture,attire,and the“Gat”in the style image by employing image sharpening and face landmark,with the GAN.The color,texture,and intensity were extracted differently based on the characteristics of each block and layer of the pre-trained VGG-16,and only the necessary elements during training were preserved using a facial landmark mask.The head area was presented using the eyebrow area to transfer the“Gat”.Furthermore,the identity of the face was retained,and style correlation was considered based on the Gram matrix.To evaluate performance,we introduced a metric using PSNR and SSIM,with an emphasis on median values through new weightings for style transfer in Korean portraits.Additionally,we have conducted a survey that evaluated the content,style,and naturalness of the transferred results,and based on the assessment,we can confidently conclude that our method to maintain the integrity of content surpasses the previous research.Our approach,enriched by landmarks preservation and diverse loss functions,including those related to“Gat”,outperformed previous researches in facial identity preservation.
文摘该文针对第二代居民身份证制证用数字相片智能检测问题进行研究并简述主要的实现技术。文章分析An il K.Ja in等提出的光线补偿方法的不足和YCbC r颜色空间在应用中的优点。一种基于环境采样卡的图像校正方法和YCbC r颜色空间上经过非线性分段色彩变换到YCb C r空间的肤色模型。该文介绍了作者在肤色模型基础上眼睛标定的具体实现技术,提出一种基于像素统计的“密度”滤波处理方法来提高肤色判断的鲁棒性。介绍了优先眼睛标定的其它数字相片规格指标的综合智能检测实现技术。
