George Fitzmaurice

Vivian Liu, Jo Vermeulen, George Fitzmaurice et al.

Text-to-image AI are capable of generating novel images for inspiration, but their applications for 3D design workflows and how designers can build 3D models using AI-provided inspiration have not yet been explored. To investigate this, we integrated DALL-E, GPT-3, and CLIP within a CAD software in 3DALL-E, a plugin that generates 2D image inspiration for 3D design. 3DALL-E allows users to construct text and image prompts based on what they are modeling. In a study with 13 designers, we found that designers saw great potential in 3DALL-E within their workflows and could use text-to-image AI to produce reference images, prevent design fixation, and inspire design considerations. We elaborate on prompting patterns observed across 3D modeling tasks and provide measures of prompt complexity observed across participants. From our findings, we discuss how 3DALL-E can merge with existing generative design workflows and propose prompt bibliographies as a form of human-AI design history.

Esen K. Tütüncü, Qian Zhou, Frederik Brudy et al.

Current AI writing tools, which rely on text prompts, poorly support the spatial and interactive nature of storytelling where ideas emerge from direct manipulation and play. We present PlayWrite, a mixed-reality system where users author stories by directly manipulating virtual characters and props. A multi-agent AI pipeline interprets these actions into Intent Frames -structured narrative beats visualized as rearrangeable story marbles on a timeline. A large language model then transforms the user's assembled sequence into a final narrative. A user study (N=13) with writers from varying domains found that PlayWrite fosters a highly improvisational and playful process. Users treated the AI as a collaborative partner, using its unexpected responses to spark new ideas and overcome creative blocks. PlayWrite demonstrates an approach for co-creative systems that move beyond text to embrace direct manipulation and play as core interaction modalities.

Erzhen Hu, Frederik Brudy, David Ledo et al.

In pre-production, filmmakers and 3D animation experts must rapidly prototype ideas to explore a film's possibilities before fullscale production, yet conventional approaches involve trade-offs in efficiency and expressiveness. Hand-drawn storyboards often lack spatial precision needed for complex cinematography, while 3D previsualization demands expertise and high-quality rigged assets. To address this gap, we present PrevizWhiz, a system that leverages rough 3D scenes in combination with generative image and video models to create stylized video previews. The workflow integrates frame-level image restyling with adjustable resemblance, time-based editing through motion paths or external video inputs, and refinement into high-fidelity video clips. A study with filmmakers demonstrates that our system lowers technical barriers for film-makers, accelerates creative iteration, and effectively bridges the communication gap, while also surfacing challenges of continuity, authorship, and ethical consideration in AI-assisted filmmaking.

Tao Long, Kendra Wannamaker, Jo Vermeulen et al.

Design thrives on feedback. However, gathering constant feedback throughout the design process can be labor-intensive and disruptive. We explore how AI can bridge this gap by providing effortless, ambient feedback. We introduce FeedQUAC, a design companion that delivers real-time AI-generated commentary from a variety of perspectives through different personas. A design probe study with eight participants highlights how designers can leverage quick yet ambient AI feedback to enhance their creative workflows. Participants highlight benefits such as convenience, playfulness, confidence boost, and inspiration from this lightweight feedback agent, while suggesting additional features, like chat interaction and context curation. We discuss the role of AI feedback, its strengths and limitations, and how to integrate it into existing design workflows while balancing user involvement. Our findings also suggest that ambient interaction is a valuable consideration for both the design and evaluation of future creativity support systems.