Summary of A Survey on Generative Ai and Llm For Video Generation, Understanding, and Streaming, by Pengyuan Zhou et al.
A Survey on Generative AI and LLM for Video Generation, Understanding, and Streaming
by Pengyuan Zhou, Lin Wang, Zhi Liu, Yanbin Hao, Pan Hui, Sasu Tarkoma, Jussi Kangasharju
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Multimedia (cs.MM)
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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 The paper explores how generative artificial intelligence (Generative AI) and large language models (LLMs) are revolutionizing video technology. It showcases the advancements in producing realistic videos, closing the gap between real-world dynamics and digital creation. The study highlights the capabilities of LLMs in video understanding, extracting meaningful information from visual content. Additionally, it discusses how LLMs enhance video streaming experiences by adapting content delivery to individual viewer preferences. This comprehensive review covers current achievements, ongoing challenges, and future possibilities for applying Generative AI and LLMs to video-related tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how AI technologies are changing video technology. It shows how AI can make videos look really real. The study also talks about how AI can understand what’s in a video and help us interact with it better. Additionally, it discusses how AI can make streaming videos more efficient and personalized for each viewer. This review covers what’s happening now, what’s still challenging, and what might happen next. |
