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Title: :  EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION
PaperId: :  23552
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23552
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Sivasankar ChittoorSiddharth Institute of Engineering & Technology
M ChanikyaSiddharth Institute of Engineering & Technology
Agepati GayathriSiddharth Institute of Engineering & Technology
Vallemma LavanyaSiddharth Institute of Engineering & Technology
Kasthuri Anil KumarSiddharth Institute of Engineering & Technology
Abhishek Kumar PalSiddharth Institute of Engineering & Technology

Abstract

INFORMATION TECHNOLOGY
Long, Distance, Traces, Patches
With the rapid progress of deepfake techniques in recent years, facial video forgery can generate highly deceptive video content and bring severe security threats. And detection of such forgery videos is much more urgent and challenging. Most existing detection methods treat the problem as a vanilla binary classification problem. In this article, the problem is treated as a special fine-grained classification problem since the differences between fake and real faces are very subtle. It is observed that most existing face forgery methods left some common artifacts in the spatial domain and time domain, including generative defects in the spatial domain and interframe inconsistencies in the time domain. And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces from a global perspective, respectively. The two components are designed using a novel long-distance attention mechanism. One component of the spatial domain is used to capture artifacts in a single frame, and the other component of the time domain is used to capture artifacts in consecutive frames. They generate attention maps in the form of patches. The attention method has a broader vision which contributes to better assembling global information and extracting local statistic information. Finally, the attention maps are used to guide the network to focus on pivotal parts of the face, just like other fine-grained classification methods.

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IJARIIE Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. "EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 5181-5187
MLA Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. "EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 5181-5187.
APA Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, & Abhishek Kumar Pal. (2024). EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 5181-5187.
Chicago Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. "EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 5181-5187.
Oxford Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. 'EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 5181-5187. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/EXPOSING_DEEP_FAKE_VIDEOS_THROUGH_LONG_RANGE_ATTENTION_ijariie23552.pdf (Accessed : ).
Harvard Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. (2024) 'EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 5181-5187IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/EXPOSING_DEEP_FAKE_VIDEOS_THROUGH_LONG_RANGE_ATTENTION_ijariie23552.pdf (Accessed : )
IEEE Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal, "EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 5181-5187, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/EXPOSING_DEEP_FAKE_VIDEOS_THROUGH_LONG_RANGE_ATTENTION_ijariie23552.pdf [Accessed : ].
Turabian Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. "EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver Sivasankar Chittoor, M Chanikya, Agepati Gayathri, Vallemma Lavanya, Kasthuri Anil Kumar, and Abhishek Kumar Pal. EXPOSING DEEP FAKE VIDEOS THROUGH LONG RANGE ATTENTION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 5181-5187. Available from: https://ijariie.com/AdminUploadPdf/EXPOSING_DEEP_FAKE_VIDEOS_THROUGH_LONG_RANGE_ATTENTION_ijariie23552.pdf
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