Abstract. The Fast Style Transfer methods have been recently proposed to transfer a photograph to an artistic style in real-time. This task
involves controlling the stroke size in the stylized results, which remains
an open challenge. In this paper, we present a stroke controllable style
transfer network that can achieve continuous and spatial stroke size control. By analyzing the factors that influence the stroke size, we propose
to explicitly account for the receptive field and the style image scales. We
propose a StrokePyramid module to endow the network with adaptive
receptive fields, and two training strategies to achieve faster convergence
and augment new stroke sizes upon a trained model respectively. By combining the proposed runtime control strategies, our network can achieve
continuous changes in stroke sizes and produce distinct stroke sizes in
different spatial regions within the same output image