Summary of A Comprehensive Survey on Human Video Generation: Challenges, Methods, and Insights, by Wentao Lei et al.
A Comprehensive Survey on Human Video Generation: Challenges, Methods, and Insights
by Wentao Lei, Jinting Wang, Fengji Ma, Guanjie Huang, Li Liu
First submitted to arxiv on: 11 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 provides a comprehensive review of human video generation, a rapidly evolving task that aims to synthesize 2D human body video sequences with generative models. The ability to generate natural and realistic human video is critical for wide-ranging applications in film, gaming, and virtual communication. Recent advancements in generative models have laid a solid foundation for the growing interest in this area. Despite significant progress, the task remains challenging due to consistency of characters, complexity of human motion, and difficulties in their relationship with the environment. The paper starts by introducing the fundamentals of human video generation and the evolution of generative models that facilitated the field’s growth. It then examines main methods employed for three key sub-tasks: text-driven, audio-driven, and pose-driven motion generation. The survey concludes by discussing current challenges and suggesting possible directions for future research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how computers can make videos of humans doing things. This is important because it could help make movies, video games, and virtual reality experiences more realistic. The researchers looked at what’s already been done in this area and identified some big challenges that need to be solved. They also talked about the different ways computers can be told what to put in the videos, like with words or sounds. |
