Eulerian Motion Guidance: Robust Image Animation via Bidirectional Geometric Consistency
Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks typically rely on Lagrangian motion guidance, where optical flow is estimated relative to the initial frame. This paper revisits the same optical-flow primitive through a more local supervision design: we use adjacent-frame Eulerian motion fields to guide generation, where the motion signal always describes a short temporal hop. This shift enables parallelized training and provides bounded-error supervision throughout the generation process. To mitigate the drift artifacts common in adjacent frame generation, we introduce a Bidirectional Geome...
| Authors | Thong Nguyen, Khoi M. Le, Cong-Duy Nguyen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 7 May 2026 |
| Last updated at source | 12 July 2026 |
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