1 research outputs found
Deep Image Matting
Image matting is a fundamental computer vision problem and has many
applications. Previous algorithms have poor performance when an image has
similar foreground and background colors or complicated textures. The main
reasons are prior methods 1) only use low-level features and 2) lack high-level
context. In this paper, we propose a novel deep learning based algorithm that
can tackle both these problems. Our deep model has two parts. The first part is
a deep convolutional encoder-decoder network that takes an image and the
corresponding trimap as inputs and predict the alpha matte of the image. The
second part is a small convolutional network that refines the alpha matte
predictions of the first network to have more accurate alpha values and sharper
edges. In addition, we also create a large-scale image matting dataset
including 49300 training images and 1000 testing images. We evaluate our
algorithm on the image matting benchmark, our testing set, and a wide variety
of real images. Experimental results clearly demonstrate the superiority of our
algorithm over previous methods.Comment: Computer Vision and Pattern Recognition 201