Text to Video Synthesis

Text-to-video synthesis aims to generate realistic videos from textual descriptions, a challenging task driving significant research. Current efforts focus on improving video quality, temporal consistency, and control over aspects like camera movement, employing architectures such as diffusion models and transformers, often incorporating techniques like video compression and motion priors to enhance efficiency and realism. This field holds substantial promise for applications in content creation, visual effects, and 3D vision, with ongoing research focused on optimizing model efficiency and expanding creative control.