Summary of Flexgen: Flexible Multi-view Generation From Text and Image Inputs, by Xinli Xu et al.
FlexGen: Flexible Multi-View Generation from Text and Image Inputs
by Xinli Xu, Wenhang Ge, Jiantao Lin, Jiawei Feng, Lie Xu, HanFeng Zhao, Shunsi Zhang, Ying-Cong Chen
First submitted to arxiv on: 14 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A flexible framework for generating controllable multi-view images is introduced, conditioned on a single-view image, text prompt, or both. The proposed approach, FlexGen, tackles challenges in controllable multi-view synthesis through additional conditioning on 3D-aware text annotations generated by GPT-4V. This enables the creation of multiple views with spatial relationships and attributes such as appearance, material properties, and metallic roughness. Experiments demonstrate enhanced multiple controllability compared to existing models, with implications for rapid 3D content creation in fields like game development, animation, and virtual reality. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary FlexGen is a new way to create many different views of an object from just one view or some text. It’s very good at making sure the views look realistic and match what you want them to be. For example, you can ask it to make a car with shiny paint or rough stone. This helps game developers, animators, and people who make virtual reality experiences create 3D content quickly and easily. |
Keywords
» Artificial intelligence » Gpt » Prompt
