HyperDepth: Learning Depth from Structured Light without Matching-Reference-Cited by-同舟云学术

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HyperDepth: Learning Depth from Structured Light without Matching

Published:2016-06 Issue: Volume: Page:
ISSN:
Container-title:2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Fanello Sean Ryan,Rhemann Christoph,Tankovich Vladimir,Kowdle Adarsh,Escolano Sergio Orts,Kim David,Izadi Shahram

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7776647/7780329/07780956.pdf?arnumber=7780956

Cited by 71 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. Depth Reconstruction with Neural Signed Distance Fields in Structured Light Systems;2024 International Conference on 3D Vision (3DV);2024-03-18

2. Adaptive depth measurement based on adversarial relevance vector regression for fringe projection profilometry;Measurement;2024-03

3. Overview of modulation techniques for spatially structured-light 3D imaging;Optics & Laser Technology;2024-02

4. An Effective Checkerboard Calibration Technique for a Stereo Camera System;2023 IEEE Pune Section International Conference (PuneCon);2023-12-14

5. Online Adaptive Disparity Estimation for Dynamic Scenes in Structured Light Systems;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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