3D Instance Segmentation

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6 papers in the last four weeks, up 100% on the four weeks before. 0.1% of all new papers.

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STEP-Parts: Geometric Partitioning of Boundary Representations for Large-Scale CAD Processing
Apr 16, 2026Shen Fan, Mikołaj Kida, Przemyslaw MusialskiGeometric Representation Learning 3D Instance Segmentation
New Jersey Institute of Technology · Warsaw University of Technology
Data Synthesis Improves 3D Myotube Instance Segmentation
Apr 16, 2026David Exler, Nils Friederich, Martin Krüger +5Synthetic Data Augmentation Image Segmentation
Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany. · Institute of Biological and Chemical Systems, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany. · CeMOS Research and Transfer Center, Technische Hochschule Mannheim, Paul-Wittsack-Straße 10, 68163 Mannheim, Germany.
Scene-Agnostic Object-Centric Representation Learning for 3D Gaussian Splatting
Apr 10, 2026Tsuheng Hsu, Guiyu Liu, Juho Kannala +13D Gaussian Splatting Unsupervised Representation Learning
Aalto University · University of Oulu
TSegAgent: Zero-Shot Tooth Segmentation via Geometry-Aware Vision-Language Agents
Mar 20, 2026Shaojie Zhuang, Lu Yin, Guangshun Wei +3Medical Imaging Medical Image Segmentation
Shandong University, Jinan 250010, China · University of Surrey, Guildford, Surrey, United Kingdom · King’s College London, London, United Kingdom
Training-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation
Dec 22, 2025Gyeongrok Oh, Youngdong Jang, Jonghyun Choi +3Panoptic Segmentation 3D Instance Segmentation
Korea University · Hyundai Motor Company · Sogang University +1
Label-Efficient 3D Forest Mapping: Self-Supervised and Transfer Learning for Instance Segmentation, Semantic Segmentation, and Species Classification
Nov 9, 2025Aldino Rizaldy, Fabian Ewald Fassnacht, Ahmed Jamal Afifi +3Self-Supervised Learning Tree Species Classification
Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Helmholtz Institute Freiberg for Resource Technology (HIF), 09599 Freiberg, Germany. · Institute of Geomatics, BOKU University, 1190 Vienna, Austria · Remote Sensing and Geoinformatics, Freie Universität Berlin, 12249 Berlin, Germany +1
RoofSeg: An edge-aware transformer-based network for end-to-end roof plane segmentation
Aug 26, 2025Siyuan You, Guozheng Xu, Pengwei Zhou +33D Point Cloud Segmentation 3D Instance Segmentation
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China · School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China · Wuhan Unversity Shenzhen Research Institute, Shenzhen 518057, China.
PointGauss: Point Cloud-Guided Multi-Object Segmentation for Gaussian Splatting
Aug 1, 2025Wentao Sun, Yiping Chen, John S. Zelek +13D Gaussian Splatting 3D Semantic Segmentation
University of Waterloo, Waterloo, ON N2L 3G1, Canada · Sun Yat-Sen University, Zhuhai 519082, China
OV-MAP: Open-Vocabulary Zero-Shot 3D Instance Segmentation Map for Robots
Jun 13, 2025Juno Kim, Yesol Park, Hye-Jung Yoon +1Robotic Perception 3D Instance Segmentation
Interdisciplinary Program in AI, Seoul National University · Artificial Intelligence Institute, Seoul National University · Department of Computer Science, Seoul National University
Voxeland: Probabilistic Instance-Aware Semantic Mapping with Evidence-based Uncertainty Quantification
Nov 13, 2024Jose-Luis Matez-Bandera, Pepe Ojeda, Javier Monroy +2Segmentation Uncertainty Estimation 3D Instance Segmentation
Machine Perception and Intelligent Robotics (MAPIR) Group, Malaga Institute for Mechatronics Engineering and Cyber-Physical Systems (IMECH.UMA), University of Malaga, Campus de Teatinos, 29071 Malaga, Spain

Apr 16, 2026, cs.GRJ/K move · Enter open · S save

STEP-Parts: Geometric Partitioning of Boundary Representations for Large-Scale CAD Processing

Shen Fan, Mikołaj Kida, Przemyslaw Musialski

New Jersey Institute of Technology · Warsaw University of Technology

Geometric Representation Learning 3D Instance Segmentation

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Many CAD learning pipelines discretize Boundary Representations (B-Reps) into triangle meshes, discarding analytic surface structure and topological adjacency and thereby weakening consistent instance-level analysis. We present STEP-Parts, a deterministic CAD-to-supervision toolchain that extracts geometric instance partitions directly from raw STEP B-Reps and transfers them to tessellated carriers through retained source-face correspondence, yielding instance labels and metadata for downstream learning and evaluation. The construction merges adjacent B-Rep faces only when they share the same analytic primitive type and satisfy a near-tangent continuity criterion. On ABC, same-primitive dihedral angles are strongly bimodal, yielding a threshold-insensitive low-angle regime for part extraction. Because the partition is defined on intrinsic B-Rep topology rather than on a particular triangulation, the resulting boundaries remain stable under changes in tessellation. Applied to the DeepCAD subset of ABC, the pipeline processes approximately 180{,}000 models in under six hours on a consumer CPU. We release code and precomputed labels, and show that STEP-Parts serves both as a tessellation-robust geometric reference and as a useful supervision source in two downstream probes: an implicit reconstruction--segmentation network and a dataset-level point-based backbone.

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