RGL-NET: A Recurrent Graph Learning framework for Progressive Part Assembly-Reference-Cited by-同舟云学术

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RGL-NET: A Recurrent Graph Learning framework for Progressive Part Assembly

Published:2022-01 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
language:
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Author:

Harish Abhinav Narayan¹,Nagar Rajendra²,Raman Shanmuganathan¹

Affiliation:

1. IIT Gandhinagar,CVIG Lab

2. IIT Jodhpur

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9706406/9706408/09706823.pdf?arnumber=9706823

Reference38 articles.

1. Form2Fit: Learning Shape Priors for Generalizable Assembly from Disassembly

2. PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes

3. Attention is all you need;vaswani,2017

4. ComplementMe

5. Can robots assemble an IKEA chair?

Cited by 4 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. Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

2. Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

3. PuzzleNet: Boundary-Aware Feature Matching for Non-Overlapping 3D Point Clouds Assembly;Journal of Computer Science and Technology;2023-05-30

4. AssembleRL: Learning to Assemble Furniture from Their Point Clouds;2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2022-10-23

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