Computer Vision / Video Analytics

Actress Kristen Stewart Co-Authored AI Style Transfer Paper

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  • Actress Kristen Stewart made her directorial debut with the short film Come Swim, which premiered at the Sundance Film Festival and uses neural style transfer as a storytelling technique.
  • The production applied the style of an impressionistic painting that inspired the film to key scenes using CUDA, GPUs on the Amazon cloud, and the cuDNN-accelerated Caffe deep learning framework.
  • A paper co-authored with an Adobe research engineer documents the project as a case study for using style transfer in a production environment.

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The Twilight actress made her directorial debut in a short film Come Swim, shown yesterday at the Sundance Film Festival and features the use of the popular neural “style transfer” technique to build its story.
The project, co-authored with an Adobe research engineer, is a great case study on the ability to use style transfer in a production. Using CUDA, GPUs on the Amazon cloud and the cuDNN-accelerated Caffe deep learning framework, they redrew key scenes in Come Swim in the style of the impressionistic painting that inspired the film.

Usage of Neural Style Transfer in Come Swim; left: content image, middle: style image, right: upsampled result.

As mentioned in the paper, GPUs played a key role in the work since they provided the computing power necessary to achieve the quality needed for the images in a reasonable amount of time.
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