Face Deepfakes -- A Comprehensive Review
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866916622400225280 |
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| author | Fernando, Tharindu Priyasad, Darshana Sridharan, Sridha Ross, Arun Fookes, Clinton |
| author_facet | Fernando, Tharindu Priyasad, Darshana Sridharan, Sridha Ross, Arun Fookes, Clinton |
| contents | In recent years, remarkable advancements in deep-fake generation technology have led to unprecedented leaps in its realism and capabilities. Despite these advances, we observe a notable lack of structured and deep analysis deepfake technology. The principal aim of this survey is to contribute a thorough theoretical analysis of state-of-the-art face deepfake generation and detection methods. Furthermore, we provide a coherent and systematic evaluation of the implications of deepfakes on face biometric recognition approaches. In addition, we outline key applications of face deepfake technology, elucidating both positive and negative applications of the technology, provide a detailed discussion regarding the gaps in existing research, and propose key research directions for further investigation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_09812 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Face Deepfakes -- A Comprehensive Review Fernando, Tharindu Priyasad, Darshana Sridharan, Sridha Ross, Arun Fookes, Clinton Computer Vision and Pattern Recognition Machine Learning In recent years, remarkable advancements in deep-fake generation technology have led to unprecedented leaps in its realism and capabilities. Despite these advances, we observe a notable lack of structured and deep analysis deepfake technology. The principal aim of this survey is to contribute a thorough theoretical analysis of state-of-the-art face deepfake generation and detection methods. Furthermore, we provide a coherent and systematic evaluation of the implications of deepfakes on face biometric recognition approaches. In addition, we outline key applications of face deepfake technology, elucidating both positive and negative applications of the technology, provide a detailed discussion regarding the gaps in existing research, and propose key research directions for further investigation. |
| title | Face Deepfakes -- A Comprehensive Review |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2502.09812 |