Painting with Bob

Benedetti, Luca; Winnemöller, Holger; Corsini, Massimiliano; Scopigno, Roberto

doi:10.1145/2642918.2647415

Cited by 52 publications

(2 citation statements)

References 24 publications

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“…For the first goal, we use the standard SUS scale and add five new evaluation indicators. These five indicators are derived from the user experience criteria of co-creation between humans and artificial intelligence designed by Oh et al [37] and the design goals proposed by Benedetii et al [38], including personalization, fun, flexibility, communication, and kickstart. Each evaluation indicator is designed on a 5-point Likert scale.…”

Section: System Evaluationmentioning

confidence: 99%

An Interactive Collaborative Creation System for Shadow Puppets Based on Smooth Generative Adversarial Networks

Yang,

Lou,

Chen

et al. 2024

CMC

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Chinese shadow puppetry has been recognized as a world intangible cultural heritage. However, it faces substantial challenges in its preservation and advancement due to the intricate and labor-intensive nature of crafting shadow puppets. To ensure the inheritance and development of this cultural heritage, it is imperative to enable traditional art to flourish in the digital era. This paper presents an Interactive Collaborative Creation System for shadow puppets, designed to facilitate the creation of high-quality shadow puppet images with greater ease. The system comprises four key functions: Image contour extraction, intelligent reference recommendation, generation network, and color adjustment, all aimed at assisting users in various aspects of the creative process, including drawing, inspiration, and content generation. Additionally, we propose an enhanced algorithm called Smooth Generative Adversarial Networks (SmoothGAN), which exhibits more stable gradient training and a greater capacity for generating highresolution shadow puppet images. Furthermore, we have built a new dataset comprising high-quality shadow puppet images to train the shadow puppet generation model. Both qualitative and quantitative experimental results demonstrate that SmoothGAN significantly improves the quality of image generation, while our system efficiently assists users in creating high-quality shadow puppet images, with a SUS scale score of 84.4. This study provides a valuable theoretical and practical reference for the digital creation of shadow puppet art.

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Section: System Evaluationmentioning

confidence: 99%

An Interactive Collaborative Creation System for Shadow Puppets Based on Smooth Generative Adversarial Networks

Yang,

Lou,

Chen

et al. 2024

CMC

View full text Add to dashboard Cite

show abstract

“…an eraser that erases everything under the cursor) against a smart toolset (e.g. an eraser that erases similar color regions under the cursor) and draws from literature in creativity support tools [3]. PortraitSketch provides a set of automatic assistance algorithms for adjusting user strokes while drawing to achieve a certain portrait aesthetic [35].…”

Section: Scaffolds On Designmentioning

confidence: 99%