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Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases
March 18, 2024, 4:44 a.m. | Rio Aguina-Kang, Maxim Gumin, Do Heon Han, Stewart Morris, Seung Jean Yoo, Aditya Ganeshan, R. Kenny Jones, Qiuhong Anna Wei, Kailiang Fu, Daniel Ritc
cs.CV updates on arXiv.org arxiv.org
Abstract: We present a system for generating indoor scenes in response to text prompts. The prompts are not limited to a fixed vocabulary of scene descriptions, and the objects in generated scenes are not restricted to a fixed set of object categories -- we call this setting indoor scene generation. Unlike most prior work on indoor scene generation, our system does not require a large training dataset of existing 3D scenes. Instead, it leverages the world …
abstract arxiv cs.cv cs.gr databases generated llm object objects prompts set synthesis text type universe
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