电讯技术2025，Vol.65Issue(8)：1196-1203,8.DOI:10.20079/j.issn.1001-893x.241118001
融合多结构信息和GAN的遮挡人脸修复算法
An Occluded Face Inpainting Algorithm Integrating Multi-structure Information and GAN
摘要
Abstract
For the problems that the face image inpainting results of existing algorithms often suffer from problems such as edge blurring and structural distortion,an occluded face inpainting algorithm based on multi-structure information fusion and generative adversarial network(GAN)is proposed.The inpainting module and information fusion and regeneration module are built,in which the inpainting module is composed of two gated convolution-based U-Net networks to achieve constraints and guidance for each other and produce good edge and image inpainting information.The generated information is fused and regenerated using bidirectional gated feature fusion modules and context feature aggregation modules to achieve precise completion of missing parts in the information fusion and regeneration module.For the complete face images generated by the information fusion and inpainting module,the edge discriminators and original image discriminators are adopted to optimize the parameters of the generator,further improving the inpainting effect of the algorithm.Experimental results on the public datasets Celeba-HQ and FFHQ indicate that,compared with competing algorithms,this method achieves an average improvement of 1.8%in structural similarity and an average boost of 2.1 dB in peak signal-to-noise ratio.It can effectively repair large,irregular missing areas and produce images with clear textures and well-structured details.关键词
人脸修复/信息融合/生成对抗网络/多先验属性/门卷积Key words
face inpainting/information fusion/generation adversarial network/multiple prior attribute/gate convolution分类
信息技术与安全科学引用本文复制引用
杨辉,程汉荣,王富平,甄立,王文静..融合多结构信息和GAN的遮挡人脸修复算法[J].电讯技术,2025,65(8):1196-1203,8.基金项目
陕西省科技厅重点研发计划(2024SF-YBXM-663) （2024SF-YBXM-663）
