Abstract:We propose a novel neural-network-based method to perform matting of videos depicting people that does not require additional user input such as trimaps. Our architecture achieves temporal stability of the resulting alpha mattes by using motion-estimation-based smoothing of image-segmentation algorithm outputs, combined with convolutional-LSTM modules on U-Net skip connections.We also propose a fake-motion algorithm that generates training clips for the videomatting network given photos with ground-truth alpha… Show more
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