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A lip-syncing deepfake is a digitally manipulated video in which a person's lip movements are created convincingly using AI models to match altered or entirely new audio.
“Interpretable and trustworthy deepfake detection via dynamic prototypes,”
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Z Wang, A C Bovik, H R Sheikh, and E P Simoncelli, · 2004
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“Dlib-ml: A machine learning toolkit,”
Davis E King, · 2009
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“Adam: A method for stochastic optimization,”
D P Kingma and J Ba, · 2014
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“Learning spatiotemporal features with 3d convolutional networks,”
D Tran, L Bourdev, R Fergus, L Torresani, and M Paluri, · 2015
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“Fast face-swap using convolutional neural networks,”
I Korshunova, W Shi, J Dambre, and L Theis, · 2017
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“Attention is all you need,”
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin, · 2017
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“In ictu oculi: Exposing ai created fake videos by detecting eye blinking,”
Y Li, M Chang, and S Lyu, · 2018
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“Exposing deepfake videos by detecting face warping artifacts,”
Y Li and S Lyu, · 2018
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“Transfer learning from speaker verification to multispeaker text-to-speech synthesis,”
Y Jia, Y Zhang, R Weiss, Q Wang, J Shen, F Ren, P Nguyen, R Pang, I Lopez Moreno, Y Wu, et al., · 2018
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“Deep audio-visual speech recognition,”
T Afouras, J S Chung, A Senior, O Vinyals, and A Zisserman, · 2018
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“Faceforensics++: Learning to detect manipulated facial images,”
A Rossler, D Cozzolino, et al., · 2019
Cited alongside, same era.
“Fsgan: Subject agnostic face swapping and reenactment,”
Y Nirkin, Y Keller, and T Hassner, · 2019
Cited alongside, same era.
“A lip sync expert is all you need for speech to lip generation in the wild,”
KR Prajwal, R Mukhopadhyay, V P Namboodiri, and CV Jawahar, · 2020
Cited alongside, same era.
“Celeb-df: A large-scale challenging dataset for deepfake forensics,”
Y Li, X Yang, P Sun, H Qi, and S Lyu, · 2020
Cited alongside, same era.
“Audio-driven talking face video generation with learning-based personalized head pose,”
R Yi, Z Ye, J Zhang, H Bao, and Y-J Liu, · 2020
Cited alongside, same era.
“Deepfacelab: Integrated, flexible and extensible face-swapping framework,”
“Fnevr: Neural volume rendering for face animation,”
B Zeng, B Liu, et al., · 2022
Later among the works it cites.
“Deep learning for deepfakes creation and detection: A survey,”
T Ti Nguyen, Q V H Nguyen, D T Nguyen, D T Nguyen, T Huynh-The, S Nahavandi, T T Nguyen, Q-V Pham, and C M Nguyen, · 2022
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“Lip sync matters: A novel multimodal forgery detector,”
S A Shahzad, A Hashmi, S Khan, Y-T Peng, Y Tsao, and H-M Wang, · 2022
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“Leveraging real talking faces via self-supervision for robust forgery detection,”
A Haliassos, R Mira, S Petridis, and M Pantic, · 2022
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“Deepfake detection by humans: Face swap versus lip sync,” 2023
I Sundström, · 2023
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“Integrating audio-visual features for multimodal deepfake detection,”
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I Perov, D Gao, et al., · 2020
Cited alongside, same era.
“Fakeavceleb: A novel audio-video multimodal deepfake dataset,”
H Khalid, S Tariq, M Kim, and S S Woo, · 2021
Cited alongside, same era.
“Exploring temporal coherence for more general video face forgery detection,”
Y Zheng, J Bao, D Chen, M Zeng, and F Wen, · 2021
Cited alongside, same era.
“Lips don’t lie: A generalisable and robust approach to face forgery detection,”
A Haliassos, K Vougioukas, S Petridis, and M Pantic, · 2021
Cited alongside, same era.
“Deepfakes evolution: Analysis of facial regions and fake detection performance,”
R Tolosana, S Romero-Tapiador, J Fierrez, and R Vera-Rodriguez, · 2021
Cited alongside, same era.
“Deepfake detection based on discrepancies between faces and their context,”
Y Nirkin, L Wolf, Y Keller, and T Hassner, · 2021
Cited alongside, same era.
“Kodf: A large-scale korean deepfake detection dataset,”
P Kwon, J You, G Nam, S Park, and G Chae, · 2021
Cited alongside, same era.
S Muppalla, S Jia, and S Lyu, · 2023
Later among the works it cites.
“Watch those words: Video falsification detection using word-conditioned facial motion,”
S Agarwal, L Hu, E Ng, T Darrell, H Li, and A Rohrbach, · 2023
Later among the works it cites.
“Self-supervised video forensics by audio-visual anomaly detection,”
C Feng, Z Chen, and A Owens, · 2023
Later among the works it cites.
“Implicit identity driven deepfake face swapping detection,”
B Huang, Z Wang, et al., · 2023
Later among the works it cites.
“Unsupervised multimodal deepfake detection using intra-and cross-modal inconsistencies,”
M Tian, M Khayatkhoei, J Mathai, and W AbdAlmageed, · 2023
Later among the works it cites.
“Explicit correlation learning for generalizable cross-modal deepfake detection,”
C Yu, S Jia, X Fu, J Liu, et al., · 2024
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