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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.20622 |
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| _version_ | 1866914286723399680 |
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| author | Li, Boyu Yuan, Lin-Ping Wang, Zeyu Fu, Hongbo |
| author_facet | Li, Boyu Yuan, Lin-Ping Wang, Zeyu Fu, Hongbo |
| contents | 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 potential of sketch and AI interaction to bridge the gap between intention and outcome, and demonstrate its applicability to 3D animation and video generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_20622 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation Generation Li, Boyu Yuan, Lin-Ping Wang, Zeyu Fu, Hongbo Human-Computer Interaction 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 potential of sketch and AI interaction to bridge the gap between intention and outcome, and demonstrate its applicability to 3D animation and video generation. |
| title | SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation Generation |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2601.20622 |