Mask-guided translation of high-resolution face images

Xinyue Jiang; Hongqiong Huang

doi:10.1117/12.3031162

19 July 2024 Mask-guided translation of high-resolution face images

Xinyue Jiang, Hongqiong Huang

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131812F (2024) https://doi.org/10.1117/12.3031162
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Face image translation is the transformation of an input face-labeled image from the source domain to the target domain. However, most of the current methods are for low-resolution image translation, while the high-resolution models are less effective, and problems such as loss of detail information and blurring distortion occur. Thus, a mask-guided highresolution face image translation method is proposed. First, for the problem of irrelevant background information interfering with salient region features in face images, generator introduces parameter-free attention module to obtain global information. Second, to enhance the network's ability to extract fine-grained semantic features for high-resolution faces, the backpropagation of gradients is facilitated by utilizing the improved ConvNeXt block. Finally, discriminator is upgraded to multiscale discriminator that guides generator to produce globally consistent images and finer details. Experimental results show that the proposed method outperforms mainstream models in both similarity and detail generation of image translation results on the CelebAMask-HQ dataset with a resolution of 512×512.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinyue Jiang and Hongqiong Huang "Mask-guided translation of high-resolution face images", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131812F (19 July 2024); https://doi.org/10.1117/12.3031162

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KEYWORDS

Convolution

Data modeling

Feature extraction

Image resolution

Ablation

Education and training

Image processing

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