Publications

Saliency driven image manipulation

ACM Machine Vision Applications

Publication date: March 1, 2019

Roey Mechrez, Eli Shechtman, Lihi Zelnik-Manor

Have you ever taken a picture only to find out that an unimportant background object ended up being overly salient? Or one of those team sports photographs where your favorite player blends with the rest? Wouldn't it be nice if you could tweak these pictures just a little bit so that the distractor would be attenuated and your favorite player will stand out among her peers? Manipulating images in order to control the saliency of objects is the goal of this paper. We propose an approach that considers the internal color and saliency properties of the image. It changes the saliency map via an optimization framework that relies on patch-based manipulation using only patches from within the same image to maintain its appearance characteristics. Comparing our method with previous ones shows significant improvement, both in the achieved saliency manipulation and in the realistic appearance of the resulting images.

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