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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

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

February 1, 2023

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Authors

Lin Zhao

Huazhong University of Science and Technology


Wenbing Tao

Huazhong University of Science and Technology


DOI:

10.1609/aaai.v34i07.6994


Abstract:

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.

Topics: AAAI

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HOW TO CITE:

Lin Zhao||Wenbing Tao JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds Proceedings of the AAAI Conference on Artificial Intelligence (2020) 12951-12958.

Lin Zhao||Wenbing Tao JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds AAAI 2020, 12951-12958.

Lin Zhao||Wenbing Tao (2020). JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds. Proceedings of the AAAI Conference on Artificial Intelligence, 12951-12958.

Lin Zhao||Wenbing Tao. JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.12951-12958.

Lin Zhao||Wenbing Tao. 2020. JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds. "Proceedings of the AAAI Conference on Artificial Intelligence". 12951-12958.

Lin Zhao||Wenbing Tao. (2020) "JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds", Proceedings of the AAAI Conference on Artificial Intelligence, p.12951-12958

Lin Zhao||Wenbing Tao, "JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds", AAAI, p.12951-12958, 2020.

Lin Zhao||Wenbing Tao. "JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.12951-12958.

Lin Zhao||Wenbing Tao. "JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 12951-12958.

Lin Zhao||Wenbing Tao. JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds. AAAI[Internet]. 2020[cited 2023]; 12951-12958.


ISSN: 2374-3468


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