Papers Point Cloud Segmentation
“Point Cloud Segmentation” 태그가 달린 논문 315편 · 필터 해제
COSTA: A Cluster-Centric Paradigm for Annotation-Free Open-Set Semantic Segmentation of Aerial Point Clouds with Domain Shifts
Semantic segmentation of aerial point cloud is trapped in a generalization crisis under distinct domain shifts. While test-time adaptation offers a privacy-preserving and computationally efficient way to adapt pre-traine…
Point Cloud SegmentationSemantic SegmentationTest-time AdaptationPoint CloudsLoss Landscape Topology Reveals Why Simple Baselines are Competitive at 3D Point Cloud Segmentation Under Class Imbalance
Semantic segmentation of 3D point clouds faces severe class imbalance, yet the effectiveness of specialized imbalance-aware methods from 2D computer vision remains unclear in 3D contexts. We systematically evaluate 11 im…
Point Cloud SegmentationSemantic SegmentationPoint CloudsPoint Cloud Segmentation for Autonomous Clip Positioning in Laparoscopic Cholecystectomy on a Phantom
High-risk applications in robotics, such as robot-assisted surgery, present unique challenges. These systems must be both highly precise and interpretable in order to be deployed in environments with very low tolerance f…
Point Cloud SegmentationData AugmentationPoint CloudsGeometric-Aware Hypergraph Reasoning for Novel Class Discovery in Point Cloud Segmentation
Novel class discovery in point cloud segmentation aims to transfer knowledge from known classes to automatically identify and segment unlabeled novel classes in point clouds. Existing methods mainly rely on pairwise asso…
Point Cloud SegmentationNovel Class DiscoverySemantic SegmentationPoint CloudsWHU-Infra3D: A Full-stack Multi-modal Dataset and Benchmark for 3D Roadside Infrastructure Inventory
The paradigm of digital twin cities is shifting from coarse visual mapping toward more precise and actionable digitization of urban assets. However, existing datasets predominantly focus on coarse visual perception, lack…
Point Cloud SegmentationPoint CloudsForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation
Semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the complex 3D structure of forests into actionable information for forest monitoring…
Point Cloud SegmentationInstance SegmentationPoint CloudsMonoDuo: Using One Robot Arm to Learn Bimanual Policies
Bimanual coordination is essential for many real-world manipulation tasks, yet learning bimanual robot policies is limited by the scarcity of bimanual robots and datasets. Single-arm robots, however, are widely available…
Point Cloud SegmentationHand Pose EstimationxModel-KD: Cross-modal Knowledge Distillation for 3D Scene Perception using LiDAR
Point cloud segmentation is a fundamental task in 3D scene understanding. Its progress is constrained by the high cost and time required for dense 3D annotations, making labeled samples difficult to obtain. Beyond annota…
Point Cloud SegmentationKnowledge DistillationScene UnderstandingPoint CloudsResolving Long-Tail Ambiguity in Unsupervised 3D Point Cloud Segmentation with Language Priors
Existing approaches for unsupervised 3D point cloud segmentation predominantly rely on a purely visual similarity-based learning-by-clustering paradigm, which suffers from a fundamental limitation: long-tail ambiguity. I…
Point Cloud SegmentationPoint CloudsPointGS: Semantic-Consistent Unsupervised 3D Point Cloud Segmentation with 3D Gaussian Splatting
Unsupervised point cloud segmentation is critical for embodied artificial intelligence and autonomous driving, as it mitigates the prohibitive cost of dense point-level annotations required by fully supervised methods. W…
Point Cloud SegmentationContrastive LearningAutonomous DrivingPoint CloudsContrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors
We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predicting cluster assignments or object-centric variables, the method learns a laten…
Point Cloud SegmentationRepresentation LearningGraph Neural NetworkMetric LearningUncertainty-aware Prototype Learning with Variational Inference for Few-shot Point Cloud Segmentation
Few-shot 3D semantic segmentation aims to generate accurate semantic masks for query point clouds with only a few annotated support examples. Existing prototype-based methods typically construct compact and deterministic…
Point Cloud Segmentation3D Semantic SegmentationPoint CloudsLearning Hierarchical Orthogonal Prototypes for Generalized Few-Shot 3D Point Cloud Segmentation
Generalized few-shot 3D point cloud segmentation aims to adapt to novel classes from only a few annotations while maintaining strong performance on base classes, but this remains challenging due to the inherent stability…
Point Cloud SegmentationIn-Field 3D Wheat Head Instance Segmentation From TLS Point Clouds Using Deep Learning Without Manual Labels
3D instance segmentation for laser scanning (LiDAR) point clouds remains a challenge in many remote sensing-related domains. Successful solutions typically rely on supervised deep learning and manual annotations, and con…
3D Instance SegmentationPoint Cloud SegmentationPoint CloudsSpaceSense-Bench: A Large-Scale Multi-Modal Benchmark for Spacecraft Perception and Pose Estimation
Autonomous space operations such as on-orbit servicing and active debris removal demand robust part-level semantic understanding and precise relative navigation of target spacecraft, yet collecting large-scale real data …
Monocular Depth EstimationPoint Cloud Segmentation2D Semantic SegmentationObject DetectionViewpoint Recommendation for Point Cloud Labeling through Interaction Cost Modeling
Semantic segmentation of 3D point clouds is important for many applications, such as autonomous driving. To train semantic segmentation models, labeled point cloud segmentation datasets are essential. Meanwhile, point cl…
Point Cloud SegmentationSemantic SegmentationAutonomous DrivingPoint CloudsResolving Primitive-Sharing Ambiguity in Long-Tailed TLS-Based Industrial MEP Point Cloud Segmentation via Spatial Context Constraints
In terrestrial laser scanning (TLS)-based mechanical, electrical, and plumbing (MEP) point cloud segmentation, safety-critical components such as reducers and valves are persistently misclassifed, blocking reliable engin…
Point Cloud SegmentationSyncTwin: Fast Digital Twin Construction and Synchronization for Safe Robotic Manipulation
Accurate and safe robotic manipulation under dynamic and visually occluded conditions remains a core challenge in real-world deployment. We introduce SyncTwin, a novel digital twin framework that unifies fast 3D scene re…
Point Cloud SegmentationG2P: Gaussian-to-Point Attribute Alignment for Boundary-Aware 3D Segmentation
Point cloud segmentation is critical for 3D scene understanding. However, sparse and irregular point distributions provide limited appearance evidence, making geometry-only features insufficient to distinguish objects wi…
Point Cloud SegmentationScene UnderstandingPoint CloudsRethinking Multimodal Few-Shot 3D Point Cloud Segmentation: From Fused Refinement to Decoupled Arbitration
In this paper, we revisit multimodal few-shot 3D point cloud semantic segmentation (FS-PCS), identifying a conflict in "Fuse-then-Refine" paradigms: the "Plasticity-Stability Dilemma." In addition, CLIP's inter-class con…
Point Cloud SegmentationSemantic Segmentation