The Joy of Neural Painting
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Abstract (arXiv)
Neural Painters is a class of models that follows a GAN framework to generate brushstrokes, which are then composed to create paintings. GANs are great generative models for AI Art but they are known to be notoriously difficult to train. To overcome GAN's limitations and to speed up the Neural Painter training, we applied Transfer Learning to the process reducing it from days to only hours, while achieving the same level of visual aesthetics in the final paintings generated. We report our approach and results in this work.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 8 references that are in the map. First posted on arXiv 19 Nov 2021.
Builds on
4 of 8 references.
References · 4
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,694
- 2015A Neural Algorithm of Artistic Stylecited by 483
- 2019Neural Painters: A learned differentiable constraint for generating brushstroke paintingscited by 28
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