Source: I work in the field. This is a current limitation, and an artifact of the data+method but not something that should be relied upon. If we do some adversary modelling, we can find two ways to work around this: 1) actively generate and search for such data; perhaps expensive for small actors but not well equipped malicious ones. 2) wait for deep learning to catch up, e.g. by extending NERFs (neural radiance fie…
> This is a current limitation The thing with any AI/ML tech is that current limitations are always underplayed by proponents. Self-driving cars will come out next year, every year. I'd say that until the tech actually exists, this is a great way to detect live deepfakes. Not using the technique just because maybe sometime in the future it won't work isn't very sound. For an extreme opponent you may need additional s…
Re: To uncover a deepfake video call, ask the caller to turn sideways
#281One thing that I haven't seen mentioned is that many of the recent articles I've seen misuse the phrase "deep fake" and usually mean "face-swap algorithm" or "look-alike". The former, I believe has been able to defeat this test for 10 years at least and the latter has always been able defeat this trick.