LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes-Reference-Cited by-同舟云学术

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LapSeg3D: Weakly Supervised Semantic Segmentation of Point Clouds Representing Laparoscopic Scenes

Published:2022-10-23 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Alt Benjamin¹,Kunz Christian²,Katic Darko¹,Younis Rayan³,Jakel Rainer¹,Muller-Stich Beat Peter³,Wagner Martin³,Mathis-Ullrich Franziska²

Affiliation:

1. B. Alt, D. Katic and R. Jäkel are with Artiminds Robotics GmbH,Karlsruhe,Germany,76131

2. Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology,Karlsruhe,Germany,76131

3. Department for General, Visceral and Transplantation Surgery, Heidelberg University Hospital,Heidelberg,Germany,69120

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981178.pdf?arnumber=9981178

Reference23 articles.

1. Segmentation and labelling of intraoperative laparoscopic images using structure from point cloud;haouchine;2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI),0

2. Endoscopic Vision Challenge 2021: HeiChole Surgical Workflow Analysis and Full Scene Segmentation (HeiSurF);bodenstedt,2021

3. CloudCompare,0

4. Pointnet++: Deep hierarchical feature learning on point sets in a metric space;qi;Adv Neural Inf Process Syst,2017

5. Pointnet: Deep learning on point sets for 3d classification and segmentation;qi;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,0

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