Assessing the Use of Face Swapping Methods as Face Anonymizers in Videos
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918036409155584 |
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| author | Muştu, Mustafa İzzet Ekenel, Hazım Kemal |
| author_facet | Muştu, Mustafa İzzet Ekenel, Hazım Kemal |
| contents | The increasing demand for large-scale visual data, coupled with strict privacy regulations, has driven research into anonymization methods that hide personal identities without seriously degrading data quality. In this paper, we explore the potential of face swapping methods to preserve privacy in video data. Through extensive evaluations focusing on temporal consistency, anonymity strength, and visual fidelity, we find that face swapping techniques can produce consistent facial transitions and effectively hide identities. These results underscore the suitability of face swapping for privacy-preserving video applications and lay the groundwork for future advancements in anonymization focused face-swapping models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_20985 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Assessing the Use of Face Swapping Methods as Face Anonymizers in Videos Muştu, Mustafa İzzet Ekenel, Hazım Kemal Computer Vision and Pattern Recognition The increasing demand for large-scale visual data, coupled with strict privacy regulations, has driven research into anonymization methods that hide personal identities without seriously degrading data quality. In this paper, we explore the potential of face swapping methods to preserve privacy in video data. Through extensive evaluations focusing on temporal consistency, anonymity strength, and visual fidelity, we find that face swapping techniques can produce consistent facial transitions and effectively hide identities. These results underscore the suitability of face swapping for privacy-preserving video applications and lay the groundwork for future advancements in anonymization focused face-swapping models. |
| title | Assessing the Use of Face Swapping Methods as Face Anonymizers in Videos |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2505.20985 |