SIRA-PCR: Sim-to-Real Adaptation for 3D Point Cloud Registration-Reference-Cited by-同舟云学术

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SIRA-PCR: Sim-to-Real Adaptation for 3D Point Cloud Registration

Published:2023-10-01 Issue: Volume:29 Page:14348-14359
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Chen Suyi¹,Xu Hao²,Li Ru³,Liu Guanghui¹,Fu Chi-Wing²,Liu Shuaicheng¹

Affiliation:

1. University of Electronic Science and Technology of China

2. The Chinese University of Hong Kong

3. Harbin Institute of Technology

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377707.pdf?arnumber=10377707

Reference86 articles.

1. Self-Supervised Learning for Domain Adaptation on Point Clouds

2. Joint Supervised and Self-Supervised Learning for 3D Real World Challenges

3. SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

4. PointNetLK: Robust & Efficient Point Cloud Registration Using PointNet

5. PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency

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1. Learning compact and overlap-biased interactions for point cloud registration;Neurocomputing;2024-09

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