#deepwarp

Eye Gaze Warping

These are still images, plus DeepWarp eye retargeting and some depth trickery.

There’s a lot of things that come to mind every time I see a project like this: The Treachery of Images; the flowering of a new era of computationally-aided art; how image enhancement will soon let us make bigger, sharper neural-network outputs.

Photography isn’t truth: the image is not the thing. From the very beginning, composition and photomontage made photos less-than-totally-reliable, but the degree to which they can be altered today makes chain-of-custody more important than ever.

(For that matter, photorealism is not reality. The images we accept as “real” are different for different cultures and contexts: a film without cuts appears dreamlike and unreal.)

But that’s the very ability that lets us create images that are more-real-than-real, to express things artistically that artists could previously only do with great labor, if at all. While there are still technical and economic barriers to making these tools widely accessible, it’s a lot more accessible than, say, a Renaissance artist who had to employ an entire studio of assistants and cater solely to patrons who could afford it.

And, of course, the blurriness that limits how far this technique can currently be pushed will be alleviated as new deep learning research continues.

New Post has been published on https://www.aneddoticamagazine.com/deepwarp/

DeepWarp

Try out the DeepWarp. DEMO

https://www.aneddoticamagazine.com/wp-content/uploads/circular.webm

“In this work, we consider the task of generating highly-realistic images of a given face with a redirected gaze. We treat this problem as a specific instance of conditional image generation, and suggest a new deep architecture that can handle this task very well as revealed by numerical comparison with prior art and a user study. Our deep architecture performs coarse-to-fine warping with an additional intensity correction of individual pixels. All these operations are performed in a feed-forward manner, and the parameters associated with different operations are learned jointly in the end-to-end fashion. After learning, the resulting neural network can synthesize images with manipulated gaze, while the redirection angle can be selected arbitrarily from a certain range and provided as an input to the network.” Yaroslav Ganin, Daniil Kononenko, Diana Sungatullina, Victor Lempitsky

New Post has been published on https://www.aneddoticamagazine.com/deepwarp/

DeepWarp

Try out the DeepWarp. DEMO

https://www.aneddoticamagazine.com/wp-content/uploads/circular.webm

“In this work, we consider the task of generating highly-realistic images of a given face with a redirected gaze. We treat this problem as a specific instance of conditional image generation, and suggest a new deep architecture that can handle this task very well as revealed by numerical comparison with prior art and a user study. Our deep architecture performs coarse-to-fine warping with an additional intensity correction of individual pixels. All these operations are performed in a feed-forward manner, and the parameters associated with different operations are learned jointly in the end-to-end fashion. After learning, the resulting neural network can synthesize images with manipulated gaze, while the redirection angle can be selected arbitrarily from a certain range and provided as an input to the network.” Yaroslav Ganin, Daniil Kononenko, Diana Sungatullina, Victor Lempitsky

@DeepWarp

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DeepWarp: Gaze Manipulation

Continuing our infinite series on things you can do with neural nets, DeepWarp is a research project that can change which way the eyes in a photograph are looking. This is more than just tweaking the iris and pupil: because it learned what moving eyes look like from being trained on photographs of real eyes, it also knows how to change the eyelids and the subtle muscle changes around the eyes. 

I’d like to see what this could do for game characters, of the old-school character-portrait-in-the-interface type, like Dungeon Master and Doom. Paint a bunch of character portraits, hook them up to a facial-expression generator, and have a wide variety of emoting to react to what happens in the game.