Unsupervised OmniMVS: Efficient Omnidirectional Depth Inference via Establishing Pseudo-Stereo Supervision-Reference-Cited by-同舟云学术

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Unsupervised OmniMVS: Efficient Omnidirectional Depth Inference via Establishing Pseudo-Stereo Supervision

Published:2023-10-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Chen Zisong¹,Lin Chunyu¹,Nie Lang¹,Liao Kang¹,Zhao Yao¹

Affiliation:

1. Institute of Information Science, Beijing Jiaotong University,Beijing,China,100044

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10341341/10341342/10342332.pdf?arnumber=10342332

Reference32 articles.

1. Cube Padding for Weakly-Supervised Saliency Prediction in 360° Videos

2. Spherical cnns;Cohen;arXiv preprint,2018

3. SphereNet: Learning Spherical Representations for Detection and Classification in Omnidirectional Images

4. Deformable Convolutional Networks

5. Unsupervised Monocular Depth Estimation with Left-Right Consistency

Cited by 2 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. Geometry-Informed Distance Candidate Selection for Adaptive Lightweight Omnidirectional Stereo Vision with Fisheye Images;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. CasOmniMVS: Cascade Omnidirectional Depth Estimation with Dynamic Spherical Sweeping;Applied Sciences;2024-01-06

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