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ACM Multimedia 2025Generative AI: Generative Multimedia

Multi-Object Sketch Animation with Grouping and Motion Trajectory Priors

Guotao Liang, Juncheng Hu 0001, Ximing Xing, Jing Zhang 0017, Qian Yu 0002

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3746027.3754502 ↗

摘要

We introduce GroupSketch, a novel method for vector sketch animation that effectively handles multi-object interactions and complex motions. Existing approaches struggle with these scenarios, either being limited to single-object cases or suffering from temporal inconsistency and poor generalization. To address these limitations, our method adopts a two-stage pipeline comprising Motion Initialization and Motion Refinement. In the first stage, the input sketch is interactively divided into semantic groups and key frames are defined, enabling the generation of a coarse animation via interpolation. In the second stage, we propose a Group-based Displacement Network (GDN), which refines the coarse animation by predicting group-specific displacement fields, leveraging priors from a text-to-video model. GDN further incorporates specialized modules, such as Context-conditioned Feature Enhancement (CCFE), to improve temporal consistency. Extensive experiments demonstrate that our approach significantly outperforms existing methods in generating high-quality, temporally consistent animations for complex, multi-object sketches, thus expanding the practical applications of sketch animation.