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.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
08:49 MIN
The technical process behind creating real-time deepfakes
The AI Elections: How Technology Could Shape Public Sentiment
31:01 MIN
Addressing the societal risks of deepfakes and misinformation
Building Your Own Classification Model with JavaScript - Coffee with Developers - Carly Richmond
20:04 MIN
The danger of deepfakes and the liar's dividend
The Four Horsemen of the Information Apocalypse: Taming the Wild West of Information Overload
00:09 MIN
Understanding the rapid evolution of generative AI tools
HR ROBO SAPIENS: Decoding AI Agents and Workflow Automation for Modern Recruitment
21:49 MIN
The serious threat of malicious and illegal AI use
The shadows that follow the AI generative models
13:23 MIN
Demonstrating deepfake attacks and social engineering
The AI Elections: How Technology Could Shape Public Sentiment
00:37 MIN
How generative AI fundamentally changes cybersecurity threats
WWC24 - Chris Wysopal, Helmut Reisinger and Johannes Steger - Fighting Digital Threats in the Age of AI
21:20 MIN
Playing the "Is It (F)ake?" game with the audience
Mastering Image Classification: A Journey with Cakes
Featured Partners
Related Videos
30:02The AI Elections: How Technology Could Shape Public Sentiment
Martin Förtsch & Thomas Endres
24:49Deep Fakes: The Lies We Can’t See
George Proorocu
30:38In the Dawn of the AI: Understanding and implementing AI-generated images
Timo Zander
29:54AI'll Be Back: Generative AI in Image, Video, and Audio Production
Fabian Pottbäcker, Thomas Endres & Martin Foertsch
31:19Skynet wants your Passwords! The Role of AI in Automating Social Engineering
Wolfgang Ettlinger & Alexander Hurbean
56:55Multimodal Generative AI Demystified
Ekaterina Sirazitdinova
29:27Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative
David Estevez
27:34Confuse, Obfuscate, Disrupt: Using Adversarial Techniques for Better AI and True Anonymity
David vonThenen
From learning to earning
Jobs that call for the skills explored in this talk.
