Self-Supervised Segmentation for Terracotta Warrior Point Cloud (EGG-Net)
At present, our team focuses on cultural relics restoration and fragment splicing research. In the research process of terracotta warrior splicing, we find that the existing calibrated fragment data is relatively small, which is not enough for related research. Therefore, we need to calibrate and se...
Main Authors: | Yao Hu, Guohua Geng, Kang Li, Bao Guo, Pengbo Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9691380/ |
Similar Items
-
Measurement and analysis of facial features of terracotta warriors based on high-precision 3D point clouds
by: Yungang Hu, et al.
Published: (2022-03-01) -
AMS-Net: An Attention-Based Multi-Scale Network for Classification of 3D Terracotta Warrior Fragments
by: Jie Liu, et al.
Published: (2021-09-01) -
SPPD: A Novel Reassembly Method for 3D Terracotta Warrior Fragments Based on Fracture Surface Information
by: Wenmin Yao, et al.
Published: (2021-08-01) -
Microscopic Imaging Technology Assisted Dynamic Monitoring and Restoration of Micron-Level Cracks in the Painted Layer of Terracotta Warriors and Horses of the Western Han Dynasty
by: Juanli Wang, et al.
Published: (2022-02-01) -
Terracottas in the Mediterranean Through Time II
by: Adi Erlich
Published: (2018-04-01)