University of Oulu

K. H. M. Cheng, Z. Yu, H. Chen and G. Zhao, "Benchmarking 3D Face De-Identification with Preserving Facial Attributes," 2022 IEEE International Conference on Image Processing (ICIP), Bordeaux, France, 2022, pp. 656-660, doi: 10.1109/ICIP46576.2022.9897232.

Benchmarking 3D face de-identification with preserving facial attributes

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Author: Cheng, Kevin H. M.1; Yu, Zitong1; Chen, Haoyu1;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-01-13


Privacy with the use of face images is becoming a major concern in civilians’ applications. Recent studies have exploited privacy protection methods by means of facial attributes editing or de-identifying face images. Altering attributes causes loss of information for facial analysis while most de-identification studies did not quantitatively evaluate how well facial attributes are preserved. Moreover, state-of-the-art face analysis utilized 3D information for better performance. Existing face privacy studies only focusing in 2D domain is a key limitation towards the compatibility of more advanced 3D face analysis. This paper presents the first study on the possibility of 3D face de-identification with preserving facial attributes. We systematically evaluate the performance of 2D/3D face/facial attribute recognition and develop 2D/3D de-identification methods with preserving facial attributes using Auto Encoder and Generative Adversarial Networks approaches. We present comprehensive and reproducible experimental results using a publicly available 3D face database with facial attribute annotations for benchmarking and further research.

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Series: IEEE International Conference on Image Processing
ISSN: 1522-4880
ISSN-E: 2381-8549
ISSN-L: 1522-4880
ISBN: 978-1-6654-9620-9
Pages: 656 - 660
DOI: 10.1109/icip46576.2022.9897232
Host publication: 2022 IEEE International Conference on Image Processing (ICIP)
Conference: IEEE International Conference on Image Processing
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was supported by the Academy of Finland for Academy Professor project EmotionAI (grants 336116, 345122) and Infotech Oulu, as well as the CSC-IT Center for Science, Finland, for computational resources.
Academy of Finland Grant Number: 336116
Detailed Information: 336116 (Academy of Finland Funding decision)
345122 (Academy of Finland Funding decision)
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