Thomas Endres & Martin Förtsch & Jonas Mayer
Deepfakes in Realtime - How Neural Networks Are Changing Our World
#1about 4 minutes
The danger and deception of deepfake technology
An introductory example using a fake Obama video highlights the potential for misinformation and the importance of public awareness.
#2about 4 minutes
Differentiating fakes from true deepfakes
A breakdown of related but distinct technologies like lip syncing, face swapping, and real-time reenactment clarifies what constitutes a genuine deepfake.
#3about 13 minutes
How traditional deepfakes are made with Deep Face Lab
The original deepfake workflow involves preparing a dataset with FaceNet, training a shared autoencoder, and then running inference to generate the final video.
#4about 10 minutes
Building a real-time deepfake pipeline
To achieve real-time performance, the original pipeline is modified with faster face segmentation using MobileNet and U-Net, and image inpainting to remove the original head.
#5about 8 minutes
Using GANs to improve deepfake image quality
Generative Adversarial Networks (GANs) are introduced to the training process, where a generator and a discriminator compete to produce more realistic and artifact-free faces.
#6about 2 minutes
Live demo and limitations of data-driven models
A live demonstration shows the real-time head replacement and reveals a key limitation where the model can only reproduce expressions seen in its training data.
#7about 4 minutes
Applications in entertainment and detecting fake news
Deepfakes offer a cost-effective alternative to CGI in the movie industry and can also be used to train discriminator models for detecting fake news.
#8about 2 minutes
The future of deepfakes beyond face swapping
The next evolution of deepfake technology will likely involve higher resolutions, full-body manipulation, and real-time voice cloning to create more comprehensive fakes.
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Matching moments
04:34 MIN
The technical process behind creating real-time deepfakes
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03:11 MIN
Demonstrating deepfake attacks and social engineering
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05:13 MIN
Why automated detection tools and shallow fakes fail
The AI Elections: How Technology Could Shape Public Sentiment
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03:23 MIN
The threat of AI-generated deepfakes and voice cloning
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05:28 MIN
Addressing the societal risks of deepfakes and misinformation
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02:24 MIN
The danger of deepfakes and the liar's dividend
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05:37 MIN
The growing threat of AI-generated media manipulation
The AI Elections: How Technology Could Shape Public Sentiment
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08:14 MIN
The future and ethical challenges of AI image generation
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