Challenges and Computational Demands of Video Generation

Video generation tasks require models to learn about physical properties of the world like 3D scenes, object movements, and human actions like turning around. The additional temporal dimension in videos increases computational demands, making the task more challenging. The background in physics and mechanical engineering of the researchers inspired them to delve deeper into generative modeling to understand the physical world. They aim to develop video models that not only generate videos but also comprehend and predict real-world events. Integrating multiple modalities like language with video models could potentially ground these models more firmly in the physical world.

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