The process of manually colorizing an image is usually cumbersome, time consuming and requires significant skill, which makes it a prime target for automation. Researchers at UC Berkeley led by Alexei A. Efros, Professor of Electrical Engineering and Computer Sciences, have released a paper that outlines a new method for using deep neural networks to help aid in the colorization of images.
Aided by these deep neural networks almost anyone, even those completely lacking any artistic ability, can easily create convincing colorized images.
The group’s paper, entitled “Real-Time User Guided Colorization with Learned Deep Priors,” will be presented at SIGGRAPH 2017, a conference which highlights computer graphics research.
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