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We present a novel image editing system that generates images as the userprovides free-form mask, sketch and color as an input. Our system consist of aend-to-end trainable convolutional network. Contrary to the existing methods,our system wholly utilizes free-form user input with color and shape. Thisallows the system to respond to the user's sketch and color input, using it asa guideline to generate an image. In our particular work, we trained networkwith additional style loss which made it possible to generate realisticresults, despite large portions of the image being removed. Our proposednetwork architecture SC-FEGAN is well suited to generate high quality syntheticimage using intuitive user inputs.

SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color