On Improving Boundary Quality of Instance Segmentation in Cluttered and Chaotic Scenarios
Author:
Affiliation:
1. The Chinese University of Hong Kong,Department of Computer Science and Engineering
2. The Chinese University of Hong Kong,Department of Mechanical and Automation Engineering
Funder
China National Natural Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160261.pdf?arnumber=10160261
Reference41 articles.
1. Instance Segmentation of Visible and Occluded Regions for Finding and Picking Target from a Pile of Objects
2. BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation
3. Multi-view self-supervised deep learning for 6D pose estimation in the Amazon Picking Challenge
4. Learning Panoptic Segmentation from Instance Contours
5. what's this?''-learning to segment unknown objects from manipulation se-quences;boerdijk;IEEE Int Conf on Robotics and Automation (ICRA),0
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