CD3IS: cross dimensional 3D instance segmentation network for production workshop-Reference-Cited by-同舟云学术

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CD3IS: cross dimensional 3D instance segmentation network for production workshop

Published:2023-09-12 Issue: Volume: Page:
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Tang Zaizuo,Chen Guangzhu^ORCID,Wang Ruili,Miao Zhenlian,Dai Manna,Ma Yujun,Liao Xiaojuan

Funder

Sichuan Province Foreign and Overseas High-end Talent Introduction Program

Sichuan Province Science and Technology Support Program

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

https://link.springer.com/content/pdf/10.1007/s10845-023-02200-6.pdf

Reference29 articles.

1. Bolya, D., Zhou, C., Xiao, F., & Lee, Y. J. (2019). YOLACT: Real-time instance segmentation. In Proceedings of IEEE/CVF international conference on computer vision (ICCV) (pp. 9156–9165).

2. Chen, S., Fang, J., Zhang, Q., Liu, W., & Wang, X. (2021). Hierarchical aggregation for 3D instance segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) (pp. 15467–15476).

3. Chen, Y.-N., Dai, H., & Ding, Y. (2022). Pseudo-stereo for monocular 3D object detection in autonomous driving. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) (pp. 887–897)

4. Cheng, T., Wang, X., Huang, L., & Liu, W. (2020). Boundary-preserving mask R-CNN. In Proceedings of the European conference on computer vision (ECCV) (pp. 660–676).

5. Cheng, Y., Lin, R., Zhen, P., Hou, T., Ng, C. W., Chen, H. B., Yu, H., & Wong, N. (2022). FASSST: Fast attention based single-stage segmentation net for real-time instance segmentation. In Proceedings of the 2022 IEEE/CVF winter conference on applications of computer vision, WACV 2022 (pp. 2714–2722)

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