Uncertainty Quantification of Neural Reflectance Fields for Underwater Scenes

Uncertainty Quantification of Neural Reflectance Fields for Underwater Scenes

Neural radiance fields and neural reflectance fields are novel deep learning methods for generating novel views of 3D scenes from 2D images. To extend the neural scene representation techniques to complex underwater environments, beyond neural reflectance fields underwater (BNU) was proposed, which...

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Bibliographic Details
Main Authors: Haojie Lian, Xinhao Li, Leilei Chen, Xin Wen, Mengxi Zhang, Jieyuan Zhang, Yilin Qu
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Journal of Marine Science and Engineering
Subjects:
neural reflectance fields
underwater scenes
uncertainty quantification
Online Access:https://www.mdpi.com/2077-1312/12/2/349

Internet

https://www.mdpi.com/2077-1312/12/2/349

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