Keyframer: Empowering Animation Design using Large Language Models

February 08, 2024 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Tiffany Tseng, Ruijia Cheng, Jeffrey Nichols arXiv ID 2402.06071 Category cs.HC: Human-Computer Interaction Citations 11 Venue arXiv.org Last Checked 4 months ago
Abstract
Creating 2D animations is a complex, iterative process requiring continuous adjustments to movement, timing, and coordination of multiple elements within a scene. To support designers of varying levels of experience with animation design and implementation, we developed Keyframer, a design tool that generates animation code in response to natural language prompts, enabling users to preview rendered animations inline and edit them directly through provided editors. Through a user study with 13 novices and experts in animation design and programming, we contribute 1) a categorization of semantic prompt types for describing motion and identification of a 'decomposed' prompting style where users continually adapt their goals in response to generated output; and 2) design insights on supporting iterative refinement of animations through the combination of direct editing and natural language interfaces.
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