Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback

Understand

Large text-to-video models hold immense potential for a wide range of downstream applications.

• However, they struggle to accurately depict dynamic object interactions, often resulting in unrealistic movements and frequent violations of real-world physics.
• One solution inspired by large language models is to align generated outputs with desired outcomes using external feedback.
• In this work, we investigate the use of feedback to enhance the quality of object dynamics in text-to-video models.