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In this paper, we propose a novel deep learning based algorithm that\ncan tackle both these problems. Our deep model has two parts. The first part is\na deep convolutional encoder-decoder network that takes an image and the\ncorresponding trimap as inputs and predict the alpha matte of the image. The\nsecond part is a small convolutional network that refines the alpha matte\npredictions of the first network to have more accurate alpha values and sharper\nedges. In addition, we also create a large-scale image matting dataset\nincluding 49300 training images and 1000 testing images. We evaluate our\nalgorithm on the image matting benchmark, our testing set, and a wide variety\nof real images. 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