Dense Correspondence Learning between Key Points in 3D C.elegans Based on Depth Map Matching-Reference-Cited by-同舟云学术

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Dense Correspondence Learning between Key Points in 3D C.elegans Based on Depth Map Matching

Published:2024-05-17 Issue: Volume: Page:70-74
ISSN:
Container-title:2024 3rd International Conference on Image Processing and Media Computing (ICIPMC)
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Author:

Li Yuanyuan¹,Yang Bo¹,Wu Jun²,Qu Lei¹,Huang Haimeng¹,Tian Chong¹,Liu Chao¹,Lai Chuxiao¹

Affiliation:

1. AnHui University,Information Materials and Intelligent Sensing Laboratory of Anhui Province,HeFei,China

2. AnHui University The 38th Research Institute of China Electronics Technology Group Corporation,Information Materials and Intelligent Sensing Laboratory of Anhui Province,HeFei,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10586274/10586545/10586632.pdf?arnumber=10586632

Reference19 articles.

1. The 3D-3D Registration Problem Revisited

2. Computing and processing correspondences with functional maps

3. CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds

4. Efficient and Robust Shape Correspondence via Sparsity-Enforced Quadratic Assignment

5. Learning Combinatorial Embedding Networks for Deep Graph Matching

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