Том 7

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GAN-generated strokes extension for Paint Transformer
(2024) Poliakov, Mykhailo; Shvai, Nadiya
Neural painting produces a sequence of strokes for a given image and artistically recreates it using neural networks. In this paper, we explore a novel Transformer-based framework named the Paint Transformer to predict the parameters of a stroke set with a feed-forward neural network. The Paint Transformer achieves better painting results than previous methods with more inexpensive training and inference costs. The paper proposes a novel extension to the Paint Transformer that adds more complex GAN-generated strokes to achieve a more artistically abstract painting style than the original method. This research was originally published as a Master’s thesis [1].