Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics-Reference-Cited by-同舟云学术

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Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics

Published:2021-05-30 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Ganapathi Aditya,Sundaresan Priya,Thananjeyan Brijen,Balakrishna Ashwin,Seita Daniel,Grannen Jennifer,Hwang Minho,Hoque Ryan,Gonzalez Joseph E.,Jamali Nawid,Yamane Katsu,Iba Soshi,Goldberg Ken

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9560720/9560666/09561980.pdf?arnumber=9561980

Cited by 28 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FlingFlow: LLM-Driven Dynamic Strategies for Efficient Cloth Flattening;IEEE Robotics and Automation Letters;2024-10

2. DeFNet: deconstructed strategy for multi-step fabric folding tasks;The Journal of The Textile Institute;2024-09-12

3. Learning Keypoints for Robotic Cloth Manipulation Using Synthetic Data;IEEE Robotics and Automation Letters;2024-07

4. Dense-Descriptor Transporter Networks for Multidimensional Deformable Object Manipulation;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

5. FabricFolding: learning efficient fabric folding without expert demonstrations;Robotica;2024-03-04

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