Leveraging Transformer and CNN for Monocular 3D Point Cloud Reconstruction-Reference-Cited by-同舟云学术

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Leveraging Transformer and CNN for Monocular 3D Point Cloud Reconstruction

Published:2023-09-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Wireless for Space and Extreme Environments (WiSEE)
language:
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Author:

Zamani AmirHossein¹,Kamran Ghaffari T.²,Aghdam Amir G.¹

Affiliation:

1. Concordia University,Canada

2. Traxara Robotics Inc.,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10288582/10289128/10289421.pdf?arnumber=10289421

Reference36 articles.

1. 3D-LMNet: Latent embedding matching for accurate and diverse 3D point cloud reconstruction from a single image;mandikal,2018

2. RealPoint3D: An Efficient Generation Network for 3D Object Reconstruction From a Single Image

3. CAPNet: Continuous Approximation Projection for 3D Point Cloud Reconstruction Using 2D Supervision

4. 3D-ARNet: An accurate 3D point cloud reconstruction network from a single-image

5. Pixel2point: 3D Object Reconstruction From a Single Image Using CNN and Initial Sphere

Cited by 1 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. A High-Performance Learning-Based Framework for Monocular 3-D Point Cloud Reconstruction;IEEE Journal of Radio Frequency Identification;2024

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