Motion Customization for Generating Personalized Videos from Text Prompts

This research introduces a novel approach for customizing motion in video generation from text prompts, addressing the underexplored challenge of motion representation. The proposed Motion Embeddings enable the disentanglement of motion and appearance, facilitating more creative, customized, and controllable video generation.