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Disney Research neural face swapping technique can provide photorealistic, high resolution video

A new paper published by Disney Research in partnership with ETH Zurich describes a fully automated, neural network-based method for swapping faces in photos and videos – the first such method that results in high-resolution, megapixel resolution final results according to the researchers. That could make it suited for use in film and TV, where high resolution results are key to ensuring that the final product is good enough to reliably convince viewers as to their reality.

The researchers specifically intend this tech for use in replacing an existing actor’s performance with a substitute actor’s face, for instance when de-aging or increasing the age of someone, or potentially when portraying an actor who has passed away. They also suggest it could be used for replacing the faces of stunt doubles in cases where the conditions of a scene call for them to be used.

This new method is unique from other approaches in a number of ways, including that any face used in the set can be swapped with any recorded performance, making it possible to relatively easily re-image the actors on demand. The other is that it kindles contrast- and light conditions in a compositing step to ensure the actor looks like they were actually present in the same conditions as the scene.

You can check out the results for yourself in the video below (as the researchers point out, the effect is actually much better in moving video than in still images). There’s still a hint of ‘uncanny valley’ effect going on here, but the researchers also acknowledge that, calling this “a major step toward photo-realistic face swapping that can successfully bridge the uncanny valley” in their paper. Basically it’s a lot less nightmare fuel than other attempts I’ve seen, especially when you’ve seen the side-by-side comparisons with other techniques in the sample video. And, most notably, it works at much higher resolution, which is key for actual entertainment industry use.

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The examples presented are a super small sample, so it remains to be seen how broadly this can be applied. The subjects used appear to be primarily white, for instance. Also, there’s always the question of the ethical implication of any use of face-swapping technology, especially in video, since it could be used to fabricate credible video or photographic ‘evidence’ of something that didn’t actually happen.

Given, however, that the technology is now in development from multiple quarters, it’s essentially long past the time for debate about the ethics of its development and exploration. Instead, it’s welcome that organizations like Disney Research are following the academic path and sharing the results of their work, so that others concerned about its potential malicious use can determine ways to flag, identify and protect against any bad actors.

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