Text Driven Video Generation

Text-driven video generation aims to create videos from textual descriptions, pushing the boundaries of AI-driven content creation. Current research heavily utilizes diffusion models, often enhanced with techniques like noise rescheduling for longer videos and incorporating image prompts for finer control over subject appearance and motion. This field is significant because it bridges the gap between human language and complex visual media, with potential applications ranging from personalized video content creation to more general-purpose AI agents capable of planning and executing actions based on textual instructions.