Papers › JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds

JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds

20 Dec 2019arXiv:1912.09654archive 2025-07-28

Lin Zhao, Wenbing Tao

In this paper, we propose a novel joint instance and semantic segmentation approach, which is called JSNet, in order to address the instance and semantic segmentation of 3D point clouds simultaneously. Firstly, we build an effective backbone network to extract robust features from the raw point clouds. Secondly, to obtain more discriminative features, a point cloud feature fusion module is proposed to fuse the different layer features of the backbone network. Furthermore, a joint instance semantic segmentation module is developed to transform semantic features into instance embedding space, and then the transformed features are further fused with instance features to facilitate instance segmentation. Meanwhile, this module also aggregates instance features into semantic feature space to promote semantic segmentation. Finally, the instance predictions are generated by applying a simple mean-shift clustering on instance embeddings. As a result, we evaluate the proposed JSNet on a large-scale 3D indoor point cloud dataset S3DIS and a part dataset ShapeNet, and compare it with existing approaches. Experimental results demonstrate our approach outperforms the state-of-the-art method in 3D instance segmentation with a significant improvement in 3D semantic prediction and our method is also beneficial for part segmentation. The source code for this work is available at https://github.com/dlinzhao/JSNet.

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dlinzhao/JSNet officialmentioned in papermentioned on GitHubtfMIT report
LaureenK/JSNet_LK mentioned on GitHubtf report

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Tasks

3D Instance SegmentationClusteringInstance SegmentationSegmentationSemantic Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Instance Segmentation S3DIS JSNet mCov 54.1 #15 of 21 Archive leaderboard report
3D Instance Segmentation S3DIS JSNet mPrec 66.9 #15 of 21 Archive leaderboard report
3D Instance Segmentation S3DIS JSNet mRec 53.9 #15 of 21 Archive leaderboard report
3D Instance Segmentation S3DIS JSNet mWCov 58 #15 of 21 Archive leaderboard report
Semantic Segmentation S3DIS JSNet Mean IoU 61.7 #43 of 54 Archive leaderboard report
Semantic Segmentation S3DIS JSNet Number of params N/A #43 of 54 Archive leaderboard report
Semantic Segmentation S3DIS JSNet mAcc 71.7 #43 of 54 Archive leaderboard report
Semantic Segmentation S3DIS JSNet oAcc 88.7 #43 of 54 Archive leaderboard report
Semantic Segmentation ShapeNet JSNet Mean IoU 85.8% #3 of 5 Archive leaderboard report

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