arXiv Machine Learning

Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds

arXiv AI

Sep 16

RoofSeg: An edge-aware transformer-based network for end-to-end roof plane segmentation

arXiv:2508.19003v2 Announce Type: replace-cross Abstract: Roof plane segmentation is one of the key procedures for reconstructing three-dimensional (3D) building models at levels of detail (LoD) 2 an...

By Siyuan You, Guozheng Xu, Pengwei Zhou, Qiwen Jin, Jian Yao, Li Li

llms computer-vision

arXiv Computer Vision

Sep 21

The Role of Radiometric Features in Cross-Site Leaf-Wood Segmentation of LiDAR Point Clouds

arXiv:2609.21903v1 Announce Type: new Abstract: Leaf-wood segmentation of individual trees from LiDAR point clouds is essential for quantitative structure models (QSMs) used in non-destructive biomas...

By Roman Kaharlytskyi, Derek T. Robinson, Roberto Guglielmi

computer-vision benchmarks

arXiv Computer Vision

Sep 1

CedarCypress3D: an annotated UAV-LiDAR dataset of individual trees in planted cedar and cypress forests

arXiv:2608.30149v1 Announce Type: new Abstract: Individual tree measurements derived from Light Detection and Ranging (LiDAR) mounted on Unmanned Aerial Vehicles (UAV) provide valuable information fo...

By Katsuto Shimizu (Shikoku Research Center, Forestry and Forest Products Research Institute), Fumiaki Kitahara (Department of Forest Management, Forestry and Forest Products Research Institute), Tomohiro Nishizono (Department of Forest Management, Forestry and Forest Products Research Institute), Hideki Saito (Forestry and Forest Products Research Institute), Masayoshi Takahashi (Department of Forest Management, Forestry and Forest Products Research Institute), Shingo Obata (Hokkaido Research Center, Forestry and Forest Products Research Institute), Shunsuke Tei (Hokkaido Research Center, Forestry and Forest Products Research Institute), Naoyuki Furuya (Department of Forest Management, Forestry and Forest Products Research Institute), Tomoya Goto (Green Kogyo), Eiji Kodani (Department of Forest Management, Forestry and Forest Products Research Institute), Yusuke Yamada (Graduate School of Bioagricultural Sciences, Nagoya University)

computer-vision

arXiv AI

Jul 24

Enabling Scalable Topology Inference in Distribution Systems via Constrained Multi-Source Inference

arXiv:2607. 20480v1 Announce Type: new Abstract: Accurate distribution system topology is essential for outage localization, voltage analytics, and operation of distribution grids, yet maintaining reliable connectivity records remains challenging in practice due to heterogeneous and imperfect utility data.

By Haoran Li, Lihao Mai, Muhao Guo, Jiaqi Wu, Yang Weng

arXiv Machine Learning

Aug 11

SIP: Site in Pieces- A Dataset of Disaggregated Construction-Phase 3D Scans for Semantic Segmentation and Scene Understanding

arXiv:2512. 09062v2 Announce Type: replace-cross Abstract: Accurate 3D scene interpretation in active construction sites is essential for progress monitoring, safety assessment, and digital twin development.

By Seongyong Kim, Yong Kwon Cho

computer-vision efficiency benchmarks safety

arXiv Machine Learning

Aug 10

ArchEGraph: A Large-Scale Graph Dataset for Geometry-Topology-Physics Aligned Building Energy Modeling

arXiv:2608. 06772v1 Announce Type: new Abstract: Accurate estimation of building energy use is essential for achieving carbon neutral and sustainable buildings.

By Yihui Li, Yihui Chen, Kaidi Zha, Xiaoyue Yan, Zhexuan Yu, Shiqi Dai, Jun Xiao, Jun Yin, Ramon Elias Weber, Borong Lin

benchmarks

arXiv Machine Learning

Jun 18

Point-Cloud-Assistant Localized Statistical Channel Prediction by Tangent Gaussian Splatting

arXiv:2606. 18734v1 Announce Type: cross Abstract: Accurate, site-specific channel information is crucial for optimizing next-generation wireless networks.

By Ye Xue, Yiheng Wang, Xinhua Shao, Qi Yan, Shutao Zhang, Tsung-Hui Chang

benchmarks

arXiv Computer Vision

Sep 16

Geometry vs Structure: Graph-Based Diagnostics for LiDAR Point-Cloud Simulation Fidelity

arXiv:2609.16378v1 Announce Type: cross Abstract: Digital twins provide a scalable and cost-effective complement to real-world testing for validating autonomous-driving and advanced driver-assistance...

By Ghazal Farhani, Taufiq Rahman

agents

arXiv Computer Vision

Sep 16

SSC-Priors: Exploring Semantic and Visibility Priors to Boost Lidar Semantic Scene Completion

arXiv:2609.17413v1 Announce Type: new Abstract: This paper investigates easy strategies to boost the performance of existing networks for lidar semantic scene completion (SSC) without requiring compl...

By Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch, Gilles Puy, Renaud Marlet, Raoul de Charette

computer-vision benchmarks

arXiv Machine Learning

Sep 10

Gaussian Linear Functional Manifold Method for Massive Point Cloud Data

arXiv:2609.05744v1 Announce Type: cross Abstract: Reconstructing continuous terrain manifolds from massive, unstructured airborne LiDAR point clouds remains challenging in complex Wildland-Urban Inte...

By Hong Zhao, Tonglin Zhang, Baijian Yang, Jin Wei-Kocsis, Songlin Fei

efficiency safety

arXiv Computer Vision

Sep 17

Semantic-ITC: A Frame-wise Indoor Mobile Laser Scanning Dataset and Benchmark for Semantic Segmentation

arXiv:2609.18493v1 Announce Type: new Abstract: Semantic labels for indoor mobile laser scanning (MLS) frames remain largely absent from current point cloud semantic segmentation benchmarks, which ma...

By Haiyang Wu, Muhammad Affan, George Vosselman, Ville Lehtola

computer-vision benchmarks

arXiv AI

Sep 1

Polis: 3D Self-Supervision at City Scale

arXiv:2608.29426v1 Announce Type: cross Abstract: Reliable semantic representations derived from city-scale 3D models are increasingly important for urban analysis, infrastructure monitoring, autonom...

By Alexander Rusnak, Sophia Kovalenko, Jingru Wang, Ismail Moudden, Xiru Wang, Fr\'ed\'eric Kaplan

rag agents robotics benchmarks

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