GenEx: Generating an Explorable World Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2412.09624
Understanding, navigating, and exploring the 3D physical real world has long been a central challenge in the development of artificial intelligence. In this work, we take a step toward this goal by introducing GenEx, a system capable of planning complex embodied world exploration, guided by its generative imagination that forms priors (expectations) about the surrounding environments. GenEx generates an entire 3D-consistent imaginative environment from as little as a single RGB image, bringing it to life through panoramic video streams. Leveraging scalable 3D world data curated from Unreal Engine, our generative model is rounded in the physical world. It captures a continuous 360-degree environment with little effort, offering a boundless landscape for AI agents to explore and interact with. GenEx achieves high-quality world generation, robust loop consistency over long trajectories, and demonstrates strong 3D capabilities such as consistency and active 3D mapping. Powered by generative imagination of the world, GPT-assisted agents are equipped to perform complex embodied tasks, including both goal-agnostic exploration and goal-driven navigation. These agents utilize predictive expectation regarding unseen parts of the physical world to refine their beliefs, simulate different outcomes based on potential decisions, and make more informed choices. In summary, we demonstrate that GenEx provides a transformative platform for advancing embodied AI in imaginative spaces and brings potential for extending these capabilities to real-world exploration.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2412.09624
- https://arxiv.org/pdf/2412.09624
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405355508
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405355508Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2412.09624Digital Object Identifier
- Title
-
GenEx: Generating an Explorable WorldWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-12-12Full publication date if available
- Authors
-
Taiming Lu, Tianmin Shu, Junfei Xiao, Luoxin Ye, Jiahao Wang, Peng Cheng, Wei Chen, Daniel Khashabi, Rama Chellappa, Alan Yuille, Jieneng ChenList of authors in order
- Landing page
-
https://arxiv.org/abs/2412.09624Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2412.09624Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2412.09624Direct OA link when available
- Concepts
-
Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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