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Found 10 papers, 2 papers with code
APC2Mesh: Bridging the gap from occluded building façades to full 3D models
The benefits of having digital twins of urban buildings are numerous.
PBWR: Parametric Building Wireframe Reconstruction from Aerial LiDAR Point Clouds
In this paper, we present an end-to-end 3D building wireframe reconstruction method to regress edges directly from aerial LiDAR point clouds. Our method, named Parametric Building Wireframe Reconstruction (PBWR), takes aerial LiDAR point clouds and initial edge entities as input, and fully uses self-attention mechanism of transformers to regress edge parameters without any intermediate steps such as corner prediction.
AsymFormer: Asymmetrical Cross-Modal Representation Learning for Mobile Platform Real-Time RGB-D Semantic Segmentation
Understanding indoor scenes is crucial for urban studies.
Ranked #1 on
Real-Time Semantic Segmentation
on NYU Depth v2
A Multimodal Learning Framework for Comprehensive 3D Mineral Prospectivity Modeling with Jointly Learned Structure-Fluid Relationships
This study presents a novel multimodal fusion model for three-dimensional mineral prospectivity mapping (3D MPM), effectively integrating structural and fluid information through a deep network architecture.
Building3D: An Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds
Lack of building datasets has become a major obstacle for applying deep learning technology to specific domains such as urban modeling.
Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood.
Building3D: A Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds
Lack of building datasets has become a major obstacle for applying deep learning technology to specific domains such as urban modeling.
DRB-GAN: A Dynamic ResBlock Generative Adversarial Network for Artistic Style Transfer
The style code is modeled as the shared parameters for Dynamic ResBlocks connecting both the style encoding network and the style transfer network.
An optimal hierarchical clustering approach to segmentation of mobile LiDAR point clouds
The main contribution of this paper is that we succeed to optimize the combination of clusters in the hierarchical clustering.
Road Curb Extraction from Mobile LiDAR Point Clouds
Automatic extraction of road curbs from uneven, unorganized, noisy and massive 3D point clouds is a challenging task.
