Video Generation Model

Video generation models aim to create realistic and coherent video sequences from various inputs, such as text descriptions, images, or other videos, focusing on improving visual fidelity, temporal consistency, and user control. Current research heavily utilizes diffusion models, often incorporating techniques like attention mechanisms, multi-agent frameworks, and noise rescheduling to enhance generation quality and efficiency, addressing challenges like long video generation and multi-scene consistency. These advancements have significant implications for diverse fields, including film production, robotics, medical simulation, and the creation of more realistic and interactive digital content.