DeepFake on Face and Expression Swap: A Review
Remarkable advances have been made in deep learning, leading to the emergence of highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models to manipulate facial features to create modified identities or expressions with impressive realism. These synthetic media creation...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10285057/ |
| _version_ | 1797644897615872000 |
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| author | Saima Waseem Syed Abdul Rahman Syed Abu Bakar Bilal Ashfaq Ahmed Zaid Omar Taiseer Abdalla Elfadil Eisa Mhassen Elnour Elneel Dalam |
| author_facet | Saima Waseem Syed Abdul Rahman Syed Abu Bakar Bilal Ashfaq Ahmed Zaid Omar Taiseer Abdalla Elfadil Eisa Mhassen Elnour Elneel Dalam |
| author_sort | Saima Waseem |
| collection | DOAJ |
| description | Remarkable advances have been made in deep learning, leading to the emergence of highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models to manipulate facial features to create modified identities or expressions with impressive realism. These synthetic media creations can deceive, discredit, or blackmail individuals and threaten the integrity of the legal, political, and social systems. Consequently, researchers are actively developing techniques to detect deepfake content to preserve privacy and combat the dissemination of fabricated media. This article presents a comprehensive study examining existing methods of creating deepfake images and videos for face and expression replacement. In addition, it provides an overview of publicly available deepfake datasets for benchmarking, serving as important resources for training and evaluating deepfake detection systems. In addition, the study sheds light on the detection approaches used to identify deepfake face and expression swaps while discussing the challenges and issues involved. However, the focus of this study goes beyond identifying the existing barriers. It goes a step further by outlining future research directions and guiding future scientists to address the concerns that need to be addressed in deepfake detection methods. In this way, this paper aims to facilitate the development of robust and effective deepfake detection solutions for face and expression swaps, thereby contributing to ongoing efforts to protect the authenticity and trustworthiness of visual media. |
| first_indexed | 2024-03-11T14:38:03Z |
| format | Article |
| id | doaj.art-6b365a9cb02b4ed689fd881e4d746722 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T14:38:03Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6b365a9cb02b4ed689fd881e4d7467222023-10-30T23:00:35ZengIEEEIEEE Access2169-35362023-01-011111786511790610.1109/ACCESS.2023.332440310285057DeepFake on Face and Expression Swap: A ReviewSaima Waseem0https://orcid.org/0000-0001-7704-7059Syed Abdul Rahman Syed Abu Bakar1https://orcid.org/0000-0002-4360-6630Bilal Ashfaq Ahmed2https://orcid.org/0000-0002-3981-7558Zaid Omar3https://orcid.org/0000-0003-1032-7835Taiseer Abdalla Elfadil Eisa4Mhassen Elnour Elneel Dalam5Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, MalaysiaFaculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, MalaysiaDepartment of Electrical Engineering, The University of Lahore, Lahore, PakistanFaculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, MalaysiaDepartment of Information System-Girls Section, King Khalid University, Muhayil, Saudi ArabiaDepartment of Mathematics-Girls Section, King Khalid University, Muhayil, Saudi ArabiaRemarkable advances have been made in deep learning, leading to the emergence of highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models to manipulate facial features to create modified identities or expressions with impressive realism. These synthetic media creations can deceive, discredit, or blackmail individuals and threaten the integrity of the legal, political, and social systems. Consequently, researchers are actively developing techniques to detect deepfake content to preserve privacy and combat the dissemination of fabricated media. This article presents a comprehensive study examining existing methods of creating deepfake images and videos for face and expression replacement. In addition, it provides an overview of publicly available deepfake datasets for benchmarking, serving as important resources for training and evaluating deepfake detection systems. In addition, the study sheds light on the detection approaches used to identify deepfake face and expression swaps while discussing the challenges and issues involved. However, the focus of this study goes beyond identifying the existing barriers. It goes a step further by outlining future research directions and guiding future scientists to address the concerns that need to be addressed in deepfake detection methods. In this way, this paper aims to facilitate the development of robust and effective deepfake detection solutions for face and expression swaps, thereby contributing to ongoing efforts to protect the authenticity and trustworthiness of visual media.https://ieeexplore.ieee.org/document/10285057/Deepfakedeep learningface manipulationface swapre-enactmentmedia forensic |
| spellingShingle | Saima Waseem Syed Abdul Rahman Syed Abu Bakar Bilal Ashfaq Ahmed Zaid Omar Taiseer Abdalla Elfadil Eisa Mhassen Elnour Elneel Dalam DeepFake on Face and Expression Swap: A Review IEEE Access Deepfake deep learning face manipulation face swap re-enactment media forensic |
| title | DeepFake on Face and Expression Swap: A Review |
| title_full | DeepFake on Face and Expression Swap: A Review |
| title_fullStr | DeepFake on Face and Expression Swap: A Review |
| title_full_unstemmed | DeepFake on Face and Expression Swap: A Review |
| title_short | DeepFake on Face and Expression Swap: A Review |
| title_sort | deepfake on face and expression swap a review |
| topic | Deepfake deep learning face manipulation face swap re-enactment media forensic |
| url | https://ieeexplore.ieee.org/document/10285057/ |
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