An Interactive and Generative Approach for Chinese Shanshui Painting Document Chinese Shanshui is a landscape painting document mainly drawing mountain and water, which is popular in Chinese culture. However, it is very challenging to create this by general people. In this paper, we propose an interactive and generative approach to automatically generate the Chinese Shanshui painting documents based on usersu0027 input, where the users only need to sketch simple lines to represent their ideal landscape without any professional Shanshui painting skills. This sketchtoShanshui translation is optimized by the model of cycle Generative Adversarial Networks (GAN). To evaluate the proposed approach, we collected a large set of both sketch data and Chinese Shanshui painting data to train the model of cycleGAN, and developed an interactive system called ShanshuiDaDA (i.e., Design and Draw with AI) to generate Chinese Shanshui painting documents in realtime. The experimental results show that this system can generate satisfied Chinese Shanshui painting documents by general users.

SmartPaint: a cocreative drawing system based on generative adversarial networks Artificial intelligence (AI) has played a significant role in imitating and producing largescale designs such as ecommerce banners. However, it is less successful at creative and collaborative design outputs. Most humans express their ideas as rough sketches, and lack the professional skills to complete pleasing paintings. Existing AI approaches have failed to convert varied user sketches into artistically beautiful paintings while preserving their semantic concepts. To bridge this gap, we have developed SmartPaint, a cocreative drawing system based on generative adversarial networks (GANs), enabling a machine and a human being to collaborate in cartoon landscape painting. SmartPaint trains a GAN using triples of cartoon images, their corresponding semantic label maps, and edge detection maps. The machine can then simultaneously understand the cartoon style and semantics, along with the spatial relationships among the objects in the landscape images. The trained system receives a sketch as a semantic label map input, and automatically synthesizes its edge map for stable handling of varied sketches. It then outputs a creative and fine painting with the appropriate style corresponding to the humanxe2x80x99s sketch. Experiments confirmed that the proposed SmartPaint system successfully generates highquality cartoon paintings.