SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation Generation
Boyu Li, Lin-Ping Yuan, Zeyu Wang, Hongbo Fu

TL;DR
This paper introduces SketchDynamics, a novel interaction paradigm allowing users to express dynamic animation intent through free-form sketches, enabling more intuitive and flexible content creation in animation and video generation.
Contribution
It presents a new sketch-based interface for conveying dynamic intent to AI models, addressing limitations of fixed commands and enabling natural, human-centered animation workflows.
Findings
Sketches effectively convey motion with minimal input.
User involvement is essential to resolve sketch ambiguity.
Sketches can guide video refinement visually.
Abstract
Sketching provides an intuitive way to convey dynamic intent in animation authoring (i.e., how elements change over time and space), making it a natural medium for automatic content creation. Yet existing approaches often constrain sketches to fixed command tokens or predefined visual forms, overlooking their freeform nature and the central role of humans in shaping intention. To address this, we introduce an interaction paradigm where users convey dynamic intent to a vision-language model via free-form sketching, instantiated here in a sketch storyboard to motion graphics workflow. We implement an interface and improve it through a three-stage study with 24 participants. The study shows how sketches convey motion with minimal input, how their inherent ambiguity requires users to be involved for clarification, and how sketches can visually guide video refinement. Our findings reveal the…
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Taxonomy
TopicsHuman Motion and Animation · Interactive and Immersive Displays · Artificial Intelligence in Games
