Researchers who build creativity support tools (CSTs) define abstractions and software representations that align with user needs to give users the power to accomplish tasks. However, these specifications also structure and limit how users can and should think, act, and express themselves. Thus, tool designers unavoidably exert power over their users by enacting a ``normative ground'' through their tools. Drawing on interviews with 11 creative practitioners, tool designers, and CST researchers, we offer a definition of empowerment in the context of creative practice, build a preliminary theory of how power relationships manifest in CSTs, and explain why researchers have had trouble addressing these concepts in the past. We re-examine CST literature through a lens of power and argue that mitigating power imbalances at the level of technical design requires enabling users in both vertical movement along levels of abstraction as well as horizontal movement between tools through interoperable representations. A lens of power is one possible orientation that lets us recognize the methodological shifts required towards building ``artistic support tools.''
https://doi.org/10.1145/3586183.3606831
Creativity Support Tools (CSTs) aid in the efficient and effective composition of creative content, such as picture books. However, many existing CSTs only allow for mono-modal creation, whereas previous studies have become theoretically and technically mature to support multi-modal innovative creations. To overcome this limitation, we introduce XCreation, a novel CST that leverages generative AI to support cross-modal storybook creation. Nevertheless, directly deploying AI models to CSTs can still be problematic as they are mostly black-box architectures that are not comprehensible to human users. Therefore, we integrate an interpretable entity-relation graph to intuitively represent picture elements and their relations, improving the usability of the underlying generative structures. Our between-subject user study demonstrates that XCreation supports continuous plot creation with increased creativity, controllability, usability, and interpretability. XCreation is applicable to various scenarios, including interactive storytelling and picture book creation, thanks to its multimodal nature.
https://doi.org/10.1145/3586183.3606826
Vector graphics are an industry-standard way to represent and share visual designs. Designers frequently source and incorporate styles from existing designs into their work. Unfortunately, popular design tools are not well suited for this task. We present VST, Vector Style Transfer, a novel design tool for flexibly transferring visual styles between vector graphics. The core of VST lies in leveraging automation while respecting designers' tastes and the subjectivity inherent to style transfer. In VST, designers tune a cross-design element correspondence and customize which style attributes to change. We report results from a user study in which designers used VST to control style transfer between several designs, including designs participants created with external tools beforehand. VST shows that enabling design correspondence tuning and customization is one way to support interactive, flexible style transfer.
https://doi.org/10.1145/3586183.3606751
Linework on 3D animated characters is an important aspect of stylized looks for films. We present CurveCrafter, a system allowing animators to create new lines on 3D models and to edit the shape and opacity of silhouette curves. Our tools allow users to draw, redraw, erase, edit and retime user created curves. Silhouette curves can have their shape edited or reverted, and their opacity erased or revealed. Our algorithm for propagating edits over tracked silhouette curves ensures temporal consistency even as curves expand and merge. Five professional animators used our system to animate lines on three shots with different characters. Additionally, the effects lead from the short film "Pete" used our system to more easily recreate edits on a film shot. CurveCrafter was able to successfully enhance the resulting animations with additional linework.
https://doi.org/10.1145/3586183.3606792
Color restoration of ancient Chinese paintings plays a significant role in Chinese culture protection and inheritance. However, traditional color restoration is challenging and time-consuming because it requires professional restorers to conduct detailed literature reviews on numerous paintings for reference colors. After that, they have to fill in the inferred colors on the painting manually. In this paper, we present PColorizor, an interactive system that integrates advanced deep-learning models and novel visualizations to ease the difficulties of color restoration. PColorizor is established on the principle of poem-painting congruence. Given a color-fading painting, we employ both explicit and implicit color guidance implied by ideorealm-congruent poems to associate reference paintings. To enable quick navigation of color schemes extracted from the reference paintings, we introduce a novel visualization based on a mountain metaphor that shows color distribution overtime at the ideorealm and imagery levels. Moreover, we demonstrate the ideorealm understood by deep learning models through intuitive visualizations to bridge the communication gap between human restorers and deep learning models. We also adopt intelligent color-filling techniques to accelerate manual color restoration further. To evaluate PColorizor, we collaborate with domain experts to conduct two case studies to collect their feedback. The results suggest that PColorizor could be beneficial in enabling the effective restoration of color-fading paintings.
https://doi.org/10.1145/3586183.3606814
Story ideation is a critical part of the story-writing process. It is challenging to support computationally due to its exploratory and subjective nature. Tropes, which are recurring narrative elements across stories, are essential in stories as they shape the structure of narratives and our understanding of them. In this paper, we propose to use tropes as an intermediate representation of stories to approach story ideation. We present TaleStream, a canvas system that uses tropes as building blocks of stories while providing steerable suggestions of story ideas in the form of tropes. Our trope suggestion methods leverage data from the tvtropes.org wiki. We find that 97\% of the time, trope suggestions generated by our methods provide better story ideation materials than random tropes. Our system evaluation suggests that TaleStream can support writers’ creative flow and greatly facilitates story development. Tropes, as a rich lexicon of narratives with available examples, play a key role in TaleStream and hold promise for story-creation support systems.
https://doi.org/10.1145/3586183.3606807