Video Generation

FloVD can generate camera-controllable videos using optical flow maps to show motion.

TVG can create smooth transition videos between two images without needing training. It uses diffusion models and Gaussian Process Regression for high-quality results and adds controls for better timing.

MCVD can generate videos and predict future and past frames using a masked conditional score-based diffusion model. It achieves high quality and diversity in generated frames, excelling in various video synthesis tasks.