Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation

Alexander Raistrick, Lingjie Mei, Karhan Kayan, David Yan, Yiming Zuo, Beining Han, Hongyu Wen, Meenal Parakh, Stamatis Alexandropoulos, Lahav Lipson, Zeyu Ma, Jia Deng; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 21783-21794

Abstract


We introduce Infinigen Indoors a Blender-based procedural generator of photorealistic indoor scenes. It builds upon the existing Infinigen system which focuses on natural scenes but expands its coverage to indoor scenes by introducing a diverse library of procedural indoor assets including furniture architecture elements appliances and other day-to-day objects. It also introduces a constraint-based arrangement system which consists of a domain-specific language for expressing diverse constraints on scene composition and a solver that generates scene compositions that maximally satisfy the constraints. We provide an export tool that allows the generated 3D objects and scenes to be directly used for training embodied agents in real-time simulators such as Omniverse and Unreal. Infinigen Indoors is open-sourced under the BSD license. Please visit infinigen.org for code and videos.

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[bibtex]
@InProceedings{Raistrick_2024_CVPR, author = {Raistrick, Alexander and Mei, Lingjie and Kayan, Karhan and Yan, David and Zuo, Yiming and Han, Beining and Wen, Hongyu and Parakh, Meenal and Alexandropoulos, Stamatis and Lipson, Lahav and Ma, Zeyu and Deng, Jia}, title = {Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2024}, pages = {21783-21794} }