Point Cloud Classification

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2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Toward a foundation model for forest point clouds
Sep 21, 2026Yuanwen Yue, Stefano Puliti, Damien Robert +73D Foundation Models Point Cloud Classification
ETH Zurich · University of Oxford · Norwegian Institute of Bioeconomy Research (NIBIO) +1
Instance Segmentation and Fine-grained Classification for Urban Buildings with Adaptive Region Dividing and Spatially-Supervised Contrastive Learning
Sep 17, 2026Weiyuan Zhang, Qi Zhang, Hui HuangContrastive Learning Point Cloud Classification
Guangdong Provincial Key Laboratory of Visual Media and Multidimensional Intelligence, College of Computer Science and Software Engineering, Shenzhen University
Sign Language Recognition Using Original and Synthetic Depth Image Based Point Cloud Data Models
Aug 10, 2026Rustem Ozakar, Eyup GedikliPoint Cloud Classification Sign Language Recognition
Department of Computer Engineering Erzurum Technical University Erzurum, Turkey · Department of Computer Engineering Trabzon University Trabzon, Turkey
Damage Classification for 3D Point Cloud Data via 3D Data Analysis and Vision Foundation Model-based 2D Projections
Aug 9, 2026Evan Perez, Kalelo Dukuray, Erika Ardiles-Cruz +1Point Cloud Anomaly Detection Vision Foundation Models
Dept. of Computer Science, City College of New York, NY 10031, USA · Air Force Research Lab, Rome, NY 13441, USA
Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge
Aug 7, 2026Niclas Meyer, Stefan ReitmannPoint Cloud Classification Synthetic Data Generation
1Chemnitz University of Technology
Point-Selection Fine-Tuning Framework for Robust Point Cloud Classification
Jul 22, 2026Da Li, Chang Ma, Dongfu YinPoint Cloud Classification Parameter-Efficient Fine-Tuning
Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen), Shenzhen, China · Shenzhen University, Shenzhen, China
Point Ladder Tuning: Parameter-Efficient Hierarchical Adaptation for 3D Point Cloud Understanding
Jul 21, 2026Junlin Chang, Longhao Zou, Rui Li3D Point Cloud Segmentation Point Cloud Classification
Beihang University, Beijing · Pengcheng Laboratory, Shenzhen
Depth-Dependent Hidden-State Collapse in Dynamical System Autoencoders for LiDAR Point-Cloud Classification
Jul 16, 2026Patricia Medina, Hy P. G. LamRepresentation Collapse Latent Dynamics Modeling
Department of Mathematics New York City College of Technology, CUNY Brooklyn, NY, USA · The Graduate Center, CUNY New York, NY, USA · Department of Mathematical Sciences Worcester Polytechnic Institute Worcester, MA, USA
HyperShadow: A Benchmark for Detecting 3D Projections of Higher-Dimensional Spatial Objects
Jul 15, 2026Akshay SasiPoint Cloud Classification
Independent Researcher
ProtoPointNet: Prototype-Based Interpretable Classification of 3D Dental Point Clouds with Verifiable Spatial Activations
Jul 14, 2026George V. Jose, Thao Liang Chiam, Toby Hughes +4Prototype-Based Classification Point Cloud Classification
Adelaide Dental School, Adelaide University, Adelaide, South Australia, Australia · Australian Institute for Machine Learning, Adelaide University, Adelaide, South Australia, Australia · School of Public Health, Adelaide University, Adelaide, South Australia, Australia
Hierarchical Classification via Cascading Feature Elimination: Application to Human Phenotype Ontology-Aligned Facial Phenotyping (FaceMesh2HPO)
Jul 6, 2026Fabio Hellmann, Alexander Hustinx, Benjamin D. Solomon +4Hierarchical Classification Point Cloud Classification
1*Chair for Human-centered Artificial Intelligence, University of Augsburg, Universitätsstr. 6a, Augsburg, 86159, Bavaria, Germany. · Institute for Genomic Statistics and Bioinformatics, University of Bonn, Venusberg-Campus 1, Bonn, 53127, North Rhine-Westphalia, Germany. · 3National Human Genome Research Institute, National Institutes of2026 Health, 10 Center Dr, Bethesda, 20892, MD, United States of America.
Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification
Jun 30, 2026Aizierjiang AiersilanData Leakage Point Cloud Classification
University of Macau
A Robust Point Cloud Analysis Framework Inspired By Primary Visual Cortex
Jun 12, 2026Jisheng Dang, Dengyue Pan, Delin Deng +63D Point Cloud Segmentation Point Cloud Classification
School of Information Science and Engineering, Lanzhou University · School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China · Cloud and AI BU, Huawei, Shenzhen, Guangdong 518129, China +1
MAMVI: 3D Test-Time Adaptation via Masked Multi-View Point Clouds
Jun 11, 2026Inseok Kong, Geunyoung Jung, Jiyoung JungTest-Time Adaptation Point Cloud Classification
Department of Geo Informatics, University of Seoul · Department of Artificial Intelligence, University of Seoul
An Enhanced Geometric-Spectral Feature Learning Framework for Airborne Multispectral Point Cloud Classification
Jun 8, 2026Xian Li, Yanfeng Gu, Aleksandra PižuricaRepresentation Learning Point Cloud Classification
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China · Department of Telecommunications and Information Processing, UGent-GAIM, Ghent University, 9000 Ghent, Belgium
3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes
May 21, 2026Narges Takhtkeshha, Aldino Rizaldy, Markus Hollaus +3Remote Sensing Image Understanding Point Cloud Classification
3D Optical Metrology (3DOM) Unit, Bruno Kessler Foundation (FBK), Trento, Italy · Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria · Helmholtz-ZentrumDresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology (HIF), Freiberg, Germany +2
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation
May 16, 2026Minhas Kamal, Hiranya Garbha Kumar, Balakrishnan Prabhakaran3D Point Cloud Segmentation 3D Part Segmentation
State University of New York at Albany, USA
A Unified Non-Parametric and Interpretable Point Cloud Analysis via t-FCW Graph Representation
May 14, 2026Haijian Lai, Bowen Liu, Man Xu +43D Point Cloud Segmentation 3D Part Segmentation
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China · University of Coimbra, CISUC/LASI, DEI · Macao Polytechnic University, Macao SAR, China
Beyond Defenses: Manifold-Aligned Regularization for Intrinsic 3D Point Cloud Robustness
May 8, 2026Pedro Alonso, Chongshou Li, Tianrui LiPoint Cloud Classification Adversarial Robustness
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, China · Engineering Research Center of Sustainable Urban Intelligent Transportation, Ministry of Education, Southwest Jiaotong University, Chengdu, 611756, China
A Closed-Form Adaptive-Landmark Kernel for Certified Point-Cloud and Graph Classification
May 5, 2026Sushovan Majhi, Atish Mitra, Žiga Virk +1Point Cloud Classification Classification
Data Science, George Washington University, USA · Department of Mathematical Sciences, Montana Technological University, USA · Faculty of Computer and Information Science, University of Ljubljana, Slovenia +1
A Closed-Form Persistence-Landmark Pipeline for Certified Point-Cloud and Graph Classification
May 4, 2026Sushovan Majhi, Atish Mitra, Žiga Virk +1Point Cloud Classification Classification
Data Science, George Washington University, USA · Department of Mathematical Sciences, Montana Technological University, USA · Faculty of Computer and Information Science, University of Ljubljana, Institute IMFM, Slovenia +1
Channel-Level Relation to Attentive Aggregation with Neighborhood-Homogeneity Constraint for Point Cloud Analysis
May 4, 2026Jiaqi Shi, Jin Xiao, Xiaoguang Hu +53D Point Cloud Segmentation Point Cloud Classification
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China · Wuhan Leaddo Measuring & Control Technology, Wuhan, China · School of Artificial Intelligence, Beihang University, Beijing, China
Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES
Apr 27, 2026Matti Hyyppä, Klaara Salolahti, Eric Hyyppä +9Point Cloud Classification Tree Species Classification
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, The National Land Survey of Finland, Vuorimiehentie 5, Espoo, FI-02150, Finland
A Non-Invasive Alternative to RFID: Self-Sufficient 3D Identification of Group-Housed Livestock
Apr 24, 2026Shiva Paudel, TsungCheng Tsai, Dongyi WangBiometric Identification Animal Re-Identification
University of Arkansas Fayetteville, Arkansas USA
NeuroAPS-Net: Neuro-Anatomically Aware Point Cloud Representation for Efficient Alzheimer's Disease Classification
Apr 24, 2026Towhidul Islam, Mufti MahmudEfficient Neural Network Inference Point Cloud Classification
ICS Department, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia · SDAIA-KFUPM JRC for AI, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia · IRC for Bio Systems and Machines, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
APC: Transferable and Efficient Adversarial Point Counterattack for Robust 3D Point Cloud Recognition
Apr 17, 2026Geunyoung Jung, Soohong Kim, Inseok Kong +1Point Cloud Classification Adversarial Robustness
Department of Artificial Intelligence, University of Seoul, South Korea · Department of Geo Informatics, University of Seoul, South Korea
P3T: Prototypical Point-level Prompt Tuning with Enhanced Generalization for 3D Vision-Language Models
Apr 17, 2026Geunyoung Jung, Soohong Kim, Kyungwoo Song +1Point Cloud Classification VLM Adaptation
Department of Artificial Intelligence, University of Seoul, South Korea · Department of Applied Statistics, Yonsei University, South Korea
A novel network for classification of cuneiform tablet metadata
Mar 4, 2026Frederik HagelskjærPoint Cloud Classification Point Cloud Learning
SDU Robotics · The Mærsk Mc-Kinney Møller Institute · University of Southern Denmark +1
Structure-First Point Cloud Learning with Mapper Region Graphs
Feb 5, 2026Jeongbin You, Donggun Kim, Sejun Park +1Point Cloud Classification
Department of Mathematics Korea University

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Toward a foundation model for forest point clouds

Yuanwen Yue, Stefano Puliti, Damien Robert, Atakan Topaloğlu+6

ETH Zurich · University of Oxford · Norwegian Institute of Bioeconomy Research (NIBIO)+1

3D Foundation Models Point Cloud Classification Self-Supervised Pre-Training 3D Semantic Segmentation Point Cloud Understanding 3D Instance Segmentation

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Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models are typically specialized to a single task, sensor, and forest type, making adaptation expensive in terms of annotations, computation, and expertise. We ask whether a single pretrained model can instead learn transferable representations across diverse forest inventory settings. Inspired by recent developments in language modelling and computer vision, we take a step toward a foundation model (FM) for 3D forestry. Using LitePT as backbone, we first establish a strong supervised baseline that sets a new state of the art on forest semantic and instance segmentation, tree species classification, and age regression benchmarks. We then curate a large-scale unlabelled corpus spanning airborne, UAV, and mobile laser scanning across diverse forest ecosystems, and pretrain the same backbone using self-supervised learning. We systematically evaluate representation learning strategies by comparing training from scratch, supervised pretraining, and self-supervised pretraining across four representative forestry tasks, under varying annotation budgets. Compared with training from scratch, self-supervised pretraining accelerates model convergence and consistently improves performance when annotations are scarce. Compared with task-specific supervised pretraining, self-supervised pretraining yields more transferable representations across downstream forestry tasks. These findings identify the practical regime in which pretrained representations are most valuable and suggest that instance discrimination, rather than forest semantics, is the main remaining obstacle to a general-purpose 3D forest foundation model. Code and models are available at: https://github.com/prs-eth/ForPT.

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