2025/05/27 by Boyang Wang, Xuweiyi Chen, Wang, Boyang +5 · 4 citations
Computer Science · Engineering · #Advanced Vision and Imaging #Image Processing Techniques and Applications #Computer Graphics and Visualization Techniques
paper · pdf · doi:10.48550/arxiv.2505.21491
Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cinematic technique known as Frame In and Frame Out. Specifically, starting from image-to-video generation, users can control the objects in the image to naturally leave the scene or provide breaking new identity references to enter the scene, guided by a user-specified motion trajectory. To support this task, we introduce a new dataset that is curated semi-automatically, an efficient identity-preserving motion-controllable video Diffusion Transformer architecture, and a comprehensive evaluation protocol targeting this task. Our evaluation shows that our proposed approach significantly outperforms existing baselines.