CHOrD: Generation of Collision-Free, House-Scale, and Organized Digital
  Twins for 3D Indoor Scenes with Controllable Floor Plans and Optimal Layouts
Authors: name: Chong Su, name: Yingbin Fu, name: Zheyuan Hu, name: Jing Yang, name: Param Hanji, name: Shaojun Wang, name: Xuan Zhao, name: Cengiz Öztireli, name: Fangcheng Zhong

We introduce CHOrD, a novel framework for scalable synthesis of 3D indoor
scenes, designed to create house-scale, collision-free, and hierarchically
structured indoor digital twins. In contrast to existing methods that directly
synthesize the scene layout as a scene graph or object list, CHOrD incorporates
a 2D image-based intermediate layout representation, enabling effective
prevention of collision artifacts by successfully capturing them as
out-of-distribution (OOD) scenarios during generation. Furthermore, unlike
existing methods, CHOrD is capable of generating scene layouts that adhere to
complex floor plans with multi-modal controls, enabling the creation of
coherent, house-wide layouts robust to both geometric and semantic variations
in room structures. Additionally, we propose a novel dataset with expanded
coverage of household items and room configurations, as well as significantly
improved data quality. CHOrD demonstrates state-of-the-art performance on both
the 3D-FRONT and our proposed datasets, delivering photorealistic, spatially
coherent indoor scene synthesis adaptable to arbitrary floor plan variations.