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3D Semantic Instance Segmentation

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ScanNetV2

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Papers

DBGroup: Dual-Branch Point Grouping for Weakly Supervised 3D Semantic Instance Segmentation

2025-11-13 · Xuexun Liu, Xiaoxu Xu, Qiudan Zhang, Lin Ma 외 arxiv

Weakly supervised 3D instance segmentation is essential for 3D scene understanding, especially as the growing scale of data and high annotation costs associated with fully supervised approaches. Existing methods primaril…

3D Semantic Instance Segmentation3D Semantic Segmentation3D Instance SegmentationScene Understanding

Mask3D: Mask Transformer for 3D Semantic Instance Segmentation

2022-10-06 · Jonas Schult, Francis Engelmann, Alexander Hermans, Or Litany 외

Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques. Building on the successes of recent Transformer-base…

3D Instance Segmentation3D Semantic Instance SegmentationInstance SegmentationSegmentation+1

Box2Mask: Weakly Supervised 3D Semantic Instance Segmentation Using Bounding Boxes

2022-06-02 · Julian Chibane, Francis Engelmann, Tuan Anh Tran, Gerard Pons-Moll

Current 3D segmentation methods heavily rely on large-scale point-cloud datasets, which are notoriously laborious to annotate. Few attempts have been made to circumvent the need for dense per-point annotations. In this w…

3D Instance Segmentation3D Semantic Instance SegmentationInstance SegmentationSegmentation+1

SASO: Joint 3D Semantic-Instance Segmentation via Multi-scale Semantic Association and Salient Point Clustering Optimization

2020-06-25 · Jingang Tan, Lili Chen, Kangru Wang, Jingquan Peng 외

We propose a novel 3D point cloud segmentation framework named SASO, which jointly performs semantic and instance segmentation tasks. For semantic segmentation task, inspired by the inherent correlation among objects in …

3D Instance Segmentation3D Semantic Instance SegmentationClusteringInstance Segmentation+3

3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation

2020-06-01 · CVPR 2020 6 · Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe 외

We present 3D-MPA, a method for instance segmentation on 3D point clouds. Given an input point cloud, we propose an object-centric approach where each point votes for its object center. We sample object proposals from th…

3D Object Detection3D Semantic Instance SegmentationInstance SegmentationObject+3

3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation

2020-03-30 · Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe 외

We present 3D-MPA, a method for instance segmentation on 3D point clouds. Given an input point cloud, we propose an object-centric approach where each point votes for its object center. We sample object proposals from th…

3D Instance Segmentation3D Object Detection3D Semantic Instance SegmentationObject+1

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