Summary of Sora As An Agi World Model? a Complete Survey on Text-to-video Generation, by Joseph Cho et al.
Sora as an AGI World Model? A Complete Survey on Text-to-Video Generation
by Joseph Cho, Fachrina Dewi Puspitasari, Sheng Zheng, Jingyao Zheng, Lik-Hang Lee, Tae-Ho Kim, Choong Seon Hong, Chaoning Zhang
First submitted to arxiv on: 8 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the evolution of video generation from text, building upon previous work such as animating MNIST numbers and simulating the physical world with Sora. The authors systematically discuss the core components of text-to-video generation models, including vision, language, and temporal features, highlighting their contributions to achieving a world model. The study curates 97 impactful research articles on video synthesis using text conditions, analyzing the intricacies involved beyond plain extensions of text-to-image generation. The authors identify shortcomings in Sora-generated videos, emphasizing the need for further research in dataset creation, evaluation metrics, efficient architectures, and human-controlled generation. The paper concludes that the study of text-to-video generation is still in its infancy, requiring cross-disciplinary contributions to advance towards artificial general intelligence (AGI). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how we can create videos from text, a process that has gotten much better over the past seven years. The authors break down what makes this technology work and highlight the important parts: vision, language, and time. They also analyzed many research papers on this topic and found that it’s more complicated than just extending previous work. The paper points out some weaknesses in current video generation methods and suggests we need to do more research to make them better. Overall, the study of creating videos from text is still in its early stages and will require help from experts in many different fields to make progress towards artificial general intelligence. |
Keywords
» Artificial intelligence » Image generation
