Learning to Compose Stylistic Calligraphy Artwork with Emotions

Yuan, Shuai; Liu, Ruixue; Chen, Meng; Chen, Baoyang; Qiu, Zhijie; He, Xiaodong

doi:10.1145/3474085.3475711

Cited by 10 publications

(3 citation statements)

References 25 publications

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“…Chinese Font Generation. Most previous works formulate character image generation as image translation tasks [1,[11][12][13]. Zi2zi [1] generates stylized Chinese font generation with paired data.…”

Section: Related Workmentioning

confidence: 99%

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation

Yuan¹,

Liu²,

Chen³

et al. 2022

Preprint

Self Cite

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Previous works on font generation mainly focus on the standard print fonts where character's shape is stable and strokes are clearly separated. There is rare research on brush handwriting font generation, which involves holistic structure changes and complex strokes transfer. To address this issue, we propose a novel GAN-based image translation model by integrating the skeleton information. We first extract the skeleton from training images, then design an image encoder and a skeleton encoder to extract corresponding features. A self-attentive refined attention module is devised to guide the model to learn distinctive features between different domains. A skeleton discriminator is involved to first synthesize the skeleton image from the generated image with a pre-trained generator, then to judge its realness to the target one. We also contribute a large-scale brush handwriting font image dataset with six styles and 15,000 high-resolution images. Both quantitative and qualitative experimental results demonstrate the competitiveness of our proposed model.

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Section: Related Workmentioning

confidence: 99%

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation

Yuan¹,

Liu²,

Chen³

et al. 2022

Preprint

Self Cite

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“…Art falls within the category of art in creative and visual products, according to the United Nations Conference on Trade and Development's classification model. ey believe that the worth of creative works is primarily because it comes from deep cultural soil and contains specific cultural aspects and particular cultural values [18]. e higher the content of cultural value, the potential of its value appreciation will be greater.…”

Section: Cultural Valuementioning

confidence: 99%

Evaluation Factors and Pricing Stochastic Model of Contemporary Art

Chen

2022

Mobile Information Systems

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Contemporary art is the artwork created by currently active artists. As a result, it reflects the many complexities that shape our varied, global, and continuously changing world. Many modern artists use their work to investigate personal or cultural identity, criticize societal and institutional frameworks, or even redefine art itself. The current chaotic phenomena of art market prices has an impact on the development of art, particularly substantial price fluctuations, resulting in a number of problems that are preventing the art market from developing. The aim of this paper is to get a greater understanding of art, as well as a novel approach of evaluating art and a mathematical stochastic model for estimating its price. This paper investigates the pricing method and model by looking at the cultural basis of art, modelling, decoration, market supply and demand, product practicability, and random elements, among other things, in order to help the art market flourish and allow artists to consume. The model test results clearly demonstrate the rationality of the indicator selection, indicating that the pricing model is well designed.

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“…For instance, facial expression and heartbeat rates can be supported by computer vision and smart wristbands, respectively. In ECA-GAN [218], the calligraphy style can employ various emotions, including peaceful, happy, and sad, to adjust the structures of Chinese characters in both character and discourses levels. Furthermore, the technique of photometric stereo can further convert Chinese calligraphy into 3D virtual objects.…”

Section: Calligraphymentioning

confidence: 99%

When Creators Meet the Metaverse: A Survey on Computational Arts

Lee

Lin²,

Hu³

et al. 2021

Preprint

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The metaverse, enormous virtual-physical cyberspace, has brought unprecedented opportunities for artists to blend every corner of our physical surroundings with digital creativity. This article conducts a comprehensive survey on computational arts, in which seven critical topics are relevant to the metaverse, describing novel artworks in blended virtual-physical realities. The topics first cover the building elements for the metaverse, e.g., virtual scenes and characters, auditory, textual elements. Next, several remarkable types of novel creations in the expanded horizons of metaverse cyberspace have been reflected, such as immersive arts, robotic arts, and other user-centric approaches fuelling contemporary creative outputs. Finally, we propose several research agendas: democratising computational arts, digital privacy and safety for metaverse artists, ownership recognition for digital artworks, technological challenges, and so on. The survey also serves as introductory material for artists and metaverse technologists to begin creations in the realm of surrealistic cyberspace.CCS Concepts: • Human-centered computing → Mixed / augmented reality; Graphical user interfaces; • Computing methodologies → Machine learning approaches.

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Learning to Compose Stylistic Calligraphy Artwork with Emotions

Cited by 10 publications

References 25 publications

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation

SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation

Evaluation Factors and Pricing Stochastic Model of Contemporary Art

When Creators Meet the Metaverse: A Survey on Computational Arts

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