Researchers from Adobe Research and The Chinese University of Hong Kong created an algorithm that automatically separates subjects from their backgrounds so you can easily replace the background and apply filters to the subject.
Their research paper mentions there are good user-guided tools that support manually creating masks to separate subjects from the background, but the “tools are tedious and difficult to use, and remain an obstacle for casual photographers who want their portraits to look good.”
Using a TITAN X GPU and the cuDNN-accelerated Caffe deep learning framework, the researchers trained their convolutional neural network on 1,800 portrait images from Flickr. Their GPU-accelerated method was 20x faster than a CPU-only approach.
Portrait video segmentation is next on the radar for the researchers.
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