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Despite advancements in face morphing attack detection methods, these techniques cannot reconstruct the face images of accomplices. Existing deep learning-based face de-morphing techniques have mainly focused on identity disentanglement, overlooking the morphing factors inherent in the morphed images. This paper introduces a novel face de-morphing method to restore the identity information of accomplices by predicting the corresponding de-morphing factor. To obtain reasonable de-morphing factors, a channel-wise attention mechanism is employed to perform feature interaction, and the correlation between the morphed image and the real-time captured reference image is integrated to promote the prediction of the de-morphing factor. Furthermore, the identity information of the accomplice is restored by mapping the morphed and reference images into the StyleGAN latent space and performing inverse linear interpolation using the predicted de-morphing factor. Experimental results demonstrate the superiority of this method in restoring accomplice facial images, achieving improved restoration accuracy and image quality compared to existing techniques.<\/jats:p>","DOI":"10.3390\/s24175504","type":"journal-article","created":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T03:32:01Z","timestamp":1724643121000},"page":"5504","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Feature Interaction-Based Face De-Morphing Factor Prediction for Restoring Accomplice\u2019s Facial Image"],"prefix":"10.3390","volume":"24","author":[{"given":"Juan","family":"Cai","sequence":"first","affiliation":[{"name":"School of Physics Electronics and Intelligent Manufacturing, Huaihua University, Huaihua 418000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5100-7236","authenticated-orcid":false,"given":"Qiangqiang","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1229-2317","authenticated-orcid":false,"given":"Min","family":"Long","sequence":"additional","affiliation":[{"name":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 511370, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9651-0889","authenticated-orcid":false,"given":"Le-Bing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Huaihua University, Huaihua 418000, China"},{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6581-4633","authenticated-orcid":false,"given":"Xiangling","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,25]]},"reference":[{"key":"ref_1","unstructured":"Ferrara, M., Franco, A., and Maltoni, D. 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