Post-Doctoral Research Visit F/M Editing and Conditional Generation with Text-to-Video Generation Models
Inria
France
Summary
Develop reinforcement-learning post-training methods for diffusion-based text-to-video models to enable fine-grained conditioning, temporal consistency, and identity preservation while maintaining generative diversity for realistic, editable dynamic scenes.
