Improved Event-Based Dense Depth Estimation via Optical Flow Compensation-Reference-Cited by-同舟云学术

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Improved Event-Based Dense Depth Estimation via Optical Flow Compensation

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Shi Dianxi¹,Jing Luoxi¹,Li Ruihao²,Liu Zhe³,Wang Lin³,Xu Huachi²,Zhang Yi²

Affiliation:

1. School of Computer Science, Peking University,Beijing,China,100871

2. Artificial Intelligence Research Center (AIRC), Defense Innovation Institute,Beijing,China,100166

3. College of Computer, National University of Defense Technology,Changsha,China,410073

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160605.pdf?arnumber=10160605

Reference28 articles.

1. Robust dense depth map estimation from sparse dvs stereos;zou;Brit Mach Vis Conf,0

2. Improved Cooperative Stereo Matching for Dynamic Vision Sensors with Ground Truth Evaluation

3. Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion

4. Semi-dense 3D Reconstruction with a Stereo Event Camera

5. Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera

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. SRFNet: Monocular Depth Estimation with Fine-grained Structure via Spatial Reliability-oriented Fusion of Frames and Events;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. Event Cameras in Automotive Sensing: A Review;IEEE Access;2024

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