3 citations · 3 across the 6 of their papers we have counts for
8 papers
CRAB: Cuboid-based Representation for As-built BIM from Point Clouds
Haoran Xiong, Jing Wang, Shanshan Pan +3
As-built BIM reconstruction from point clouds demands semantic, volumetric, parametric, and editable building components, beyond 2D layouts or planar abstractions. Yet existing sca…
GRE-Diff: Gaussian Room Embeddings for Structured Layout Diffusion
Jing Wang, Haoran Xiong, Zihao Yan +2
Designing functional and aesthetically coherent floor plans requires exploring a vast space of possible room arrangements, a task that quickly becomes overwhelming for human design…
Building LOD Representation for 3D Urban Scenes
Shanshan Pan, Runze Zhang, Yilin Liu +2
The advances in 3D reconstruction technology, such as photogrammetry and LiDAR scanning, have made it easier to reconstruct accurate and detailed 3D models for urban scenes. Nevert…
Real-Time Spatial Reasoning by Mobile Robots for Reconstruction and Navigation in Dynamic LiDAR Scenes
Pengdi Huang, Mingyang Wang, Huan Tian +3
Our brain has an inner global positioning system which enables us to sense and navigate 3D spaces in real time. Can mobile robots replicate such a biological feat in a dynamic envi…
ArcPro: Architectural Programs for Structured 3D Abstraction of Sparse Points
Qirui Huang, Runze Zhang, Kangjun Liu +3
We introduce ArcPro, a novel learning framework built on architectural programs to recover structured 3D abstractions from highly sparse and low-quality point clouds. Specifically,…
Systematic Literature Review of Vision-Based Approaches to Outdoor Livestock Monitoring with Lessons from Wildlife Studies
Stacey D. Scott, Zayn J. Abbas, Feerass Ellid +6
Precision livestock farming (PLF) aims to improve the health and welfare of livestock animals and farming outcomes through the use of advanced technologies. Computer vision, combin…
Architectural Co-LOD Generation
Runze Zhang, Shanshan Pan, Chenlei Lv +2
Managing the level-of-detail (LOD) in architectural models is crucial yet challenging, particularly for effective representation and visualization of buildings. Traditional approac…
Neural Packing: from Visual Sensing to Reinforcement Learning
Juzhan Xu, Minglun Gong, Hao Zhang +2
We present a novel learning framework to solve the transport-and-packing (TAP) problem in 3D. It constitutes a full solution pipeline from partial observations of input objects via…