Self-supervised Transparent Liquid Segmentation for Robotic Pouring
Author:
Affiliation:
1. Robotics Institute at Carnegie Mellon University,Pittsburgh,PA
2. University of Notre Dame
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09812000.pdf?arnumber=9812000
Reference30 articles.
1. On the importance of visual context for data augmentation in scene understanding;IEEE Transactions on Pattern Analysis and Machine Intelligence,2019
2. Analyzing Liquid Pouring Sequences via Audio-Visual Neural Networks
3. Accurate pouring with an autonomous robot using an rgb-d camera;do;International Conference on Intelligent Autonomous Systems,2018
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