Cover Image

Enriching thermal point clouds of buildings using semantic 3D building models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Jingwei, Wysocki, Olaf, Holst, Christoph, Kolbe, Thomas H.
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MLS2LoD3: Refining low LoDs building models with MLS point clouds to reconstruct semantic LoD3 building models
by: Wysocki, Olaf, et al.
Published: (2024)

Analyzing the impact of semantic LoD3 building models on image-based vehicle localization
by: Bieringer, Antonia, et al.
Published: (2024)

Radiometric fingerprinting of object surfaces using mobile laser scanning and semantic 3D road space models
by: Schwab, Benedikt, et al.
Published: (2026)

Transferring facade labels between point clouds with semantic octrees while considering change detection
by: Schwarz, Sophia, et al.
Published: (2024)

Reconstructing facade details using MLS point clouds and Bag-of-Words approach
by: Froech, Thomas, et al.
Published: (2024)

From Propagation to Prediction: Point-level Uncertainty Evaluation of MLS Point Clouds under Limited Ground Truth
by: Xu, Ziyang, et al.
Published: (2025)

Point-level Uncertainty Evaluation of Mobile Laser Scanning Point Clouds
by: Xu, Ziyang, et al.
Published: (2025)

GBSS:a global building semantic segmentation dataset for large-scale remote sensing building extraction
by: Hu, Yuping, et al.
Published: (2024)

Classifying point clouds at the facade-level using geometric features and deep learning networks
by: Tan, Yue, et al.
Published: (2024)

InfraDiffusion: zero-shot depth map restoration with diffusion models and prompted segmentation from sparse infrastructure point clouds
by: Jing, Yixiong, et al.
Published: (2025)

Texture2LoD3: Enabling LoD3 Building Reconstruction With Panoramic Images
by: Tang, Wenzhao, et al.
Published: (2025)

RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learning
by: Luo, Yuan, et al.
Published: (2025)

SYNBUILD-3D: A large, multi-modal, and semantically rich synthetic dataset of 3D building models at Level of Detail 4
by: Mayer, Kevin, et al.
Published: (2025)

L2M-Reg: Building-level Uncertainty-aware Registration of Outdoor LiDAR Point Clouds and Semantic 3D City Models
by: Xu, Ziyang, et al.
Published: (2025)

ZAHA: Introducing the Level of Facade Generalization and the Large-Scale Point Cloud Facade Semantic Segmentation Benchmark Dataset
by: Wysocki, Olaf, et al.
Published: (2024)

A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation
by: Sarker, Sushmita, et al.
Published: (2024)

TrueCity: Real and Simulated Urban Data for Cross-Domain 3D Scene Understanding
by: Nguyen, Duc, et al.
Published: (2025)

GS4Buildings: Prior-Guided Gaussian Splatting for 3D Building Reconstruction
by: Zhang, Qilin, et al.
Published: (2025)

FacaDiffy: Inpainting Unseen Facade Parts Using Diffusion Models
by: Froech, Thomas, et al.
Published: (2025)

Impact of color and mixing proportion of synthetic point clouds on semantic segmentation
by: Zhou, Shaojie, et al.
Published: (2024)

Unsupervised semantic segmentation of urban high-density multispectral point clouds
by: Oinonen, Oona, et al.
Published: (2024)

Quality-controlled registration of urban MLS point clouds reducing drift effects by adaptive fragmentation
by: Rincon, Marco Antonio Ortiz, et al.
Published: (2025)

Mind the Domain Gap: Measuring the Domain Gap Between Real-World and Synthetic Point Clouds for Automated Driving Development
by: Duc, Nguyen, et al.
Published: (2025)

Test-time adaptation for geospatial point cloud semantic segmentation with distinct domain shifts
by: Wang, Puzuo, et al.
Published: (2024)

Unsupervised deep learning for semantic segmentation of multispectral LiDAR forest point clouds
by: Ruoppa, Lassi, et al.
Published: (2025)

CDGS: Confidence-Aware Depth Regularization for 3D Gaussian Splatting
by: Zhang, Qilin, et al.
Published: (2025)

APC2Mesh: Bridging the gap from occluded building façades to full 3D models
by: Akwensi, Perpetual Hope, et al.
Published: (2024)

Segment Any Architectural Facades (SAAF):An automatic segmentation model for building facades, walls and windows based on multimodal semantics guidance
by: Li, Peilin, et al.
Published: (2025)

PC2Model: ISPRS benchmark on 3D point cloud to model registration
by: Maboudi, Mehdi, et al.
Published: (2026)

CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps
by: Hanke, Franz, et al.
Published: (2025)

Change detection needs change information: improving deep 3D point cloud change detection
by: de Gélis, Iris, et al.
Published: (2023)

3D objects and scenes classification, recognition, segmentation, and reconstruction using 3D point cloud data: A review
by: Elharrouss, Omar, et al.
Published: (2023)

What matters when building vision-language models?
by: Laurençon, Hugo, et al.
Published: (2024)

GS4City: Hierarchical Semantic Gaussian Splatting via City-Model Priors
by: Zhang, Qilin, et al.
Published: (2026)

PLANesT-3D: A new annotated dataset for segmentation of 3D plant point clouds
by: Mertoğlu, Kerem, et al.
Published: (2024)

Semantic segmentation for building houses from wooden cubes
by: Beleacov, Ivan
Published: (2025)

3DSES: an indoor Lidar point cloud segmentation dataset with real and pseudo-labels from a 3D model
by: Mérizette, Maxime, et al.
Published: (2025)

One-class anomaly detection through color-to-thermal AI for building envelope inspection
by: Kurtser, Polina, et al.
Published: (2024)

Machine learning-enabled velocity model building with uncertainty quantification
by: Orozco, Rafael, et al.
Published: (2024)

DC3DCD: unsupervised learning for multiclass 3D point cloud change detection
by: de Gélis, Iris, et al.
Published: (2023)