Cunjun Zhang
ABSTRACT
There are many great works done in image generation. However, it is still an open problem how to generate a painting, which is meeting the aesthetic rules in specific style. Therefore, in this paper, we propose a demonstration to generate a specific painting based on users' input. In the system called AI Painting, we generate an original image from content text, transfer the image into a specific aesthetic effect, simulate the image into specific artistic genre, and illustrate the painting process.
- Alexei A. Efros and William T. Freeman. 2001. Image quilting for texture synthesis and transfer. In Conference on Computer Graphics and Interactive Techniques. 341--346. Google Scholar
Digital Library
- A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. 2009. Describing objects by their attributes. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. 1778--1785.Google Scholar
- Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2016. Image Style Transfer Using Convolutional Neural Networks. In Computer Vision and Pattern Recognition. 2414--2423.Google Scholar
- Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra. 2015. DRAW: a recurrent neural network for image generation. Computer Science (2015), 1462--1471. Google ScholarDigital Library
- Aaron Hertzmann. 1998. Painterly rendering with curved brush strokes of multiple sizes. In Conference on Computer Graphics and Interactive Techniques. 453--460. Google ScholarDigital Library
- Xun Huang and Serge Belongie. 2017. Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization. (2017).Google Scholar
- Lingyu Liang and Lianwen Jin. 2013. Image-Based Rendering for Ink Painting. (2013), 3950--3954. Google ScholarDigital Library
- Yihui Ma, Jia Jia, Yufan Hou, Yaohua Bu, and Wentao Han. 2018. Understanding the Aesthetic Styles of Social Images. In Acoustics, Speech and Signal Processing (ICASSP), 2018 IEEE International Conference on. IEEE.Google ScholarCross Ref
- Yihui Ma, Jia Jia, Suping Zhou, Jingtian Fu, Yejun Liu, and Zijian Tong. 2017. Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach. (2017).Google Scholar
- Attila Neumann. 2005. Color style transfer techniques using hue, lightness and saturation histogram matching. In Eurographics Conference on Computational Aesthetics in Graphics, Visualization and Imaging. 111--122. Google ScholarDigital Library
- Devi Parikh and Kristen Grauman. 2011. Relative attributes. Iccv 6669, 5 (2011), 503--510. Google ScholarDigital Library
- Xiaohui Wang, Jia Jia, Jiaming Yin, and Lianhong Cai. 2014. Interpretable aesthetic features for affective image classification. In IEEE International Conference on Image Processing. 3230--3234.Google Scholar
- Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas. 2017. StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks. arXiv preprint arXiv:1710.10916 (2017).Google Scholar
Index Terms
- AI Painting: An Aesthetic Painting Generation System
Recommendations
Ndebele Painting in VR
The Ndebele tribe of southern Africa consists of four subtribes. The Ndzundza is the only Ndebele group practising the decorative arts of painting and beadwork. The craft of producing striking, colourful and geometrical artwork has become their most ...
Comments