5 papers
PART: Learning 3D Part Assembly and Retrieval with Transformers
Ruchao Bao, Wenzheng Wu, Chucheng Xiang +5
3D assembly is fundamental to modern manufacturing and digital content creation. In this paper, we present PART, a unified transformer-based framework for 3D part retrieval and ass…
NaLA: A 3D Native LLM Layout Agent for High-quality 3D Scene Generation
Cheng Wan, Yongsen Mao, Wenzheng Wu +7
Recently, Large Language Models (LLMs) have emerged as promising layout agents for 3D scene generation. Existing layout agents still suffer from implausible layout generation becau…
Co-Layout: LLM-driven Co-optimization for Interior Layout
Chucheng Xiang, Ruchao Bao, Biyin Feng +4
We present a novel framework for automated interior design that combines large language models (LLMs) with grid-based integer programming to jointly optimize room layout and furnit…
Imaginarium: Vision-guided High-Quality 3D Scene Layout Generation
Xiaoming Zhu, Xu Huang, Qinghongbing Xie +8
Generating artistic and coherent 3D scene layouts is crucial in digital content creation. Traditional optimization-based methods are often constrained by cumbersome manual rules, w…
DreamMat: High-quality PBR Material Generation with Geometry- and Light-aware Diffusion Models
Yuqing Zhang, Yuan Liu, Zhiyu Xie +8
2D diffusion model, which often contains unwanted baked-in shading effects and results in unrealistic rendering effects in the downstream applications. Generating Physically Based…