Hi Reddit,

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Recently, some peeps from the Samsung AI Center in Moscow published the paper Few-Shot Adversarial Learning of Realistic Neural Talking Head Models, which quickly attracted a lot of attention due to the seemingly impressive results it can produce. However, they did not release any official implementation nor trained models, which pushed to create my own, driven by my fascination with this network.

Now, I don’t have much experience with Deep Learning myself, and the paper omits a lot of very important details, so I have been struggling to get it to work properly, even if I have been working on it from day 1. Another obstacle is the computing power necessary to run such a model for as long as it is necessary to generate results of the same quality as they show in their demo.

So, I’ve decided to release my own attempt at an implementation of this model, with the intention of finding other people with the same fascination in this project, so that we could work together and hopefully make it work just as well as in their demo.

So far I’ve gotten to the point where I have been able to produce results like these:

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https://i.redd.it/mttie6zdwq231.png

But we can still improve it much more!!!

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Here’s the link to the repo. Feel free to contribute, improve the algorithm, and upload your own trained models if you make it work! I will keep working hard on it myself!

https://github.com/grey-eye/talking-heads