{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T20:14:57Z","timestamp":1768421697437,"version":"3.49.0"},"reference-count":21,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T00:00:00Z","timestamp":1748217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Opening Project of Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing","award":["2023QYY07"],"award-info":[{"award-number":["2023QYY07"]}]},{"name":"Opening Project of Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing","award":["2025ZNSFSC0477"],"award-info":[{"award-number":["2025ZNSFSC0477"]}]},{"name":"Opening Project of Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing","award":["2024NSFSC2042"],"award-info":[{"award-number":["2024NSFSC2042"]}]},{"name":"Sichuan Provincial Natural Science Foundation","award":["2023QYY07"],"award-info":[{"award-number":["2023QYY07"]}]},{"name":"Sichuan Provincial Natural Science Foundation","award":["2025ZNSFSC0477"],"award-info":[{"award-number":["2025ZNSFSC0477"]}]},{"name":"Sichuan Provincial Natural Science Foundation","award":["2024NSFSC2042"],"award-info":[{"award-number":["2024NSFSC2042"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The natural features of the face exhibit significant symmetry. In practical applications, faces may be partially occluded due to factors like wearing masks or glasses, or the presence of other objects. Occluded-face restoration has broad application prospects in fields such as augmented reality, virtual reality, healthcare, security, etc. It is also of significant practical importance in enhancing public safety and providing efficient services. This research establishes an improved occluded-face restoration network based on facial feature points and Generative Adversarial Networks. A facial landmark prediction network is constructed based on an improved MobileNetV3-small network. On the foundation of U-Net, dilated convolutions and residual blocks are introduced to form an enhanced generator network. Additionally, an improved discriminator network is built based on Patch-GAN. Compared to the Contextual Attention network, under various occlusions, the improved face restoration network shows a maximum increase in the Peak Signal-to-Noise Ratio of 24.47%, and in the Structural Similarity Index of 24.39%, and a decrease in the Fr\u00e9chet Inception Distance of 81.1%. Compared to the Edge Connect network, under various occlusions, the improved network shows a maximum increase in the Peak Signal-to-Noise Ratio of 7.89% and in the Structural Similarity Index of 10.34%, and a decrease in the Fr\u00e9chet Inception Distance of 27.2%. Compared to the LaFIn network, under various occlusions, the improved network shows a maximum increase in the Peak Signal-to-Noise Ratio of 3.4% and in the Structural Similarity Index of 3.31%, and a decrease in the Fr\u00e9chet Inception Distance of 9.19%. These experiments show that the improved face restoration network yields better restoration results.<\/jats:p>","DOI":"10.3390\/sym17060827","type":"journal-article","created":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T04:46:38Z","timestamp":1748493998000},"page":"827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Research on Improved Occluded-Face Restoration Network"],"prefix":"10.3390","volume":"17","author":[{"given":"Shangzhen","family":"Pang","sequence":"first","affiliation":[{"name":"School of Physics and Electronic Engineering, Sichuan University of Science and Engineering, Zigong 643000, China"},{"name":"Sichuan Province University Key Laboratory of Bridge Non-Destruction Detecting and Engineering Computing, Yibin 644000, China"},{"name":"Centre for Sustainability in Advanced Electrical and Electronic Systems (CSAEES), Faculty of Engineering, Built Environment and Information Technology, SEGi University, Petaling Jaya 47810, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4192-3720","authenticated-orcid":false,"given":"Tzer Hwai Gilbert","family":"Thio","sequence":"additional","affiliation":[{"name":"Centre for Sustainability in Advanced Electrical and Electronic Systems (CSAEES), Faculty of Engineering, Built Environment and Information Technology, SEGi University, Petaling Jaya 47810, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4885-7743","authenticated-orcid":false,"given":"Fei Lu","family":"Siaw","sequence":"additional","affiliation":[{"name":"Centre for Sustainability in Advanced Electrical and Electronic Systems (CSAEES), Faculty of Engineering, Built Environment and Information Technology, SEGi University, Petaling Jaya 47810, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingju","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Engineering, Sichuan University of Science and Engineering, Zigong 643000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Lin","sequence":"additional","affiliation":[{"name":"Graduate School of Business (GSB), SEGi University, Petaling Jaya 47810, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/TIP.2004.833105","article-title":"Region filling and object removal by exemplar-based image inpainting","volume":"13","author":"Criminisi","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wu, Y., Gou, C., and Ji, Q. (2017, January 21\u201326). Simultaneous facial landmark detection, pose and deformation estimation under facial occlusion. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.606"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., and Brox, T. (2015, January 5\u20139). U-net: Convolutional networks for biomedical image segmentation. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, Munich, Germany.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref_4","unstructured":"Deepak, P., Philipp, K., Jeff, D., Trevor, D., and Alexei, A.E. (2016, January 27\u201330). Context Encoders: Feature Learning by Inpainting. Proceedings of the Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA."},{"key":"ref_5","first-page":"5576","article-title":"Free-Form Image Inpainting with Gated Convolution","volume":"28","author":"Yu","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_6","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., and Gelly, S. (2021). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. arXiv."},{"key":"ref_7","unstructured":"Wan, Z., Zhang, J., Chen, D., and Liao, J. (2022). Image Inpainting with Vision Transformers. arXiv."},{"key":"ref_8","first-page":"2672","article-title":"Generative adversarial nets","volume":"27","author":"Goodfellow","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_9","unstructured":"Howard, A., Sandler, M., Chu, G., Chen, L.C., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., and Vasudevan, V. (November, January 27). Searching for mobilenetv3. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Seoul, Republic of Korea."},{"key":"ref_10","unstructured":"Nair, V., and Hinton, G.E. (2010, January 21\u201324). Rectified linear units improve restricted boltzmann machines. Proceedings of the 27th International Conference on International Conference on Machine Learning (ICML\u201910), Haifa, Israel."},{"key":"ref_11","unstructured":"Ulyanov, D., Vedaldi, A., and Lempitsky, V. (2016). Instance normalization: The missing ingredient for fast stylization. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zheng, C., Cham, T.J., and Cai, J. (2019, January 15\u201320). Pluralistic image completion. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00153"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/S0375-9601(00)00725-8","article-title":"Extended tanh-function method and its applications to nonlinear equations","volume":"277","author":"Fan","year":"2000","journal-title":"Phys. Lett. A"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., and Efros, A.A. (2017, January 21\u201326). Image-to-image translation with conditional adversarial networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref_15","unstructured":"Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y. (2018). Spectral normalization for generative adversarial networks. arXiv."},{"key":"ref_16","unstructured":"Diederik, P.K., and Jimmy, B. (2014). Adam: A method for stochastic optimization. arXiv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: From error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"ref_18","first-page":"6626","article-title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium","volume":"30","author":"Heusel","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_19","unstructured":"Nazeri, K., Ng, E., and Joseph, T. (2019). EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. arXiv."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., and Huang, T.S. (2018, January 18\u201323). Generative Image Inpainting with Contextual Attention. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00577"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yang, Y., Guo, X., Ma, J., Ma, L., and Ling, H. (2019). LaFIn: Generative Landmark Guided Face Inpainting. arXiv.","DOI":"10.1007\/978-3-030-60633-6_2"}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/6\/827\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:40:28Z","timestamp":1760031628000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/17\/6\/827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,26]]},"references-count":21,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["sym17060827"],"URL":"https:\/\/doi.org\/10.3390\/sym17060827","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,26]]}}}