Neural painting refers to the procedure of producing a series of strokes for a given image and non-photo realistically recreating it using neural networks. We formulate the task as a set prediction problem and propose a novel Transformer based framework, dubbed Paint Transformer, to predict the parameters of a stroke set with a feed forward network. This way, our model can generate a set of strokes in parallel and obtain the final painting of size 512× 512 in near real time.
2021: Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang
https://arxiv.org/pdf/2108.03798v2.pdf
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