5 papers
SR-JEPA: Learning Predictive Latent State in 3D Scenes
Zihan Zhou, Qifu Wen, Xi Zeng
Joint-embedding predictive architectures learn by predicting latent representations of missing observations, yet many masked JEPAs are evaluated primarily through the encoders they…
minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models
Min Zhao, Hongzhou Zhu, Bokai Yan +9
Recent video diffusion foundation models have achieved remarkable progress in high-quality video generation, yet turning them into real-time interactive video world models remains…
SPATIALGEN: Layout-guided 3D Indoor Scene Generation
Chuan Fang, Heng Li, Yixun Liang +6
Creating high-fidelity 3D models of indoor environments is essential for applications in design, virtual reality, and robotics. However, manual 3D modeling remains time-consuming a…
SpatialLM: Training Large Language Models for Structured Indoor Modeling
Yongsen Mao, Junhao Zhong, Chuan Fang +5
SpatialLM is a large language model designed to process 3D point cloud data and generate structured 3D scene understanding outputs. These outputs include architectural elements lik…
From 2D CAD Drawings to 3D Parametric Models: A Vision-Language Approach
Xilin Wang, Jia Zheng, Yuanchao Hu +3
In this paper, we present CAD2Program, a new method for reconstructing 3D parametric models from 2D CAD drawings. Our proposed method is inspired by recent successes in vision-lang…