Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Review of the Chinese species of the genus Scelimena Serville, 1838 (Tetrigidae: Scelimeninae: Scelimenini).

Zootaxa·2023
Same author

Redox Neutral Radical-Relay Nickel-Catalyzed Remote Carbonylation.

Organic letters·2023
Same author

Association between the triglyceride-glucose index and cognitive impairment in China: a community population-based cross-sectional study.

Nutritional neuroscience·2023
Same author

Characteristics and prognosis of rrDLBCL with TP53 mutations and a high-risk subgroup represented by the co-mutations of DDX3X-TP53.

Cancer medicine·2023
Same author

Combustion Activation Induced Solid-State Synthesis for N, B Co-Doped Carbon/Zinc Borate Anode with a Boosting of Sodium Storage Performance.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2023
Same author

Nonlinear relationship between pulse pressure and risk of cognitive impairment: A 4-year community-based cohort study in Xi'an, China.

Journal of the neurological sciences·2023

相关实验视频

Updated: Mar 15, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.2K

AHC-NeRF:双层复杂嵌套透明物体的自主,高质量的神经重建.

Youcheng Cai, Fan Gao, Yibo Zhao

    IEEE transactions on visualization and computer graphics
    |March 13, 2026
    PubMed
    概括

    本研究介绍了AHC-NeRF,这是一种用于重建复杂透明物体的新框架. 它使用神经SDF和自适应单像素成像实现了嵌套透明物体的高质量表面重建.

    科学领域:

    • 计算机视觉 计算机视觉
    • 计算机图形 计算机图形
    • 计算成像技术的成像

    背景情况:

    • 重建透明物体是具有挑战性的,因为光的折射和反射.
    • 现有的方法难以处理复杂的嵌套对象,需要繁的视图捕捉策略.

    研究的目的:

    • 提出AHC-NeRF,一个基于SDF的自主,高质量的神经框架,用于重建双层复杂嵌套透明对象.
    • 克服现有的折射追踪方法的局限性,提高重建精度.

    主要方法:

    • 将神经SDF与单像素成像 (SPI) 结合起来,用于基于反射的外部和内部表面的重建.
    • 引入了一个可适应的SPI方法,用于加速获取点对先验.
    • 采用一种新的视图规划策略,根据获得的信息逐步选择视图.

    主要成果:

    • AHC-NeRF实现了嵌套透明物体外部和内部表面的高质量重建.
    • 适应性SPI方法可以将先前的获取速度加快1-2个数量级.
    • 拟议的景观规划策略提高了表面重建质量.

    结论:

    • 与合成和现实世界数据集的最先进方法相比,AHC-NeRF表现出优越的性能.

    更多相关视频

    Localizing Protein in 3D Neural Stem Cell Culture: a Hybrid Visualization Methodology
    21:47

    Localizing Protein in 3D Neural Stem Cell Culture: a Hybrid Visualization Methodology

    Published on: December 19, 2010

    13.2K
    Whole-mount Retinal Organoid Visualization with Cellular Resolution
    09:20

    Whole-mount Retinal Organoid Visualization with Cellular Resolution

    Published on: June 20, 2025

    1.7K

    相关实验视频

    Last Updated: Mar 15, 2026

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.2K
    Localizing Protein in 3D Neural Stem Cell Culture: a Hybrid Visualization Methodology
    21:47

    Localizing Protein in 3D Neural Stem Cell Culture: a Hybrid Visualization Methodology

    Published on: December 19, 2010

    13.2K
    Whole-mount Retinal Organoid Visualization with Cellular Resolution
    09:20

    Whole-mount Retinal Organoid Visualization with Cellular Resolution

    Published on: June 20, 2025

    1.7K
  • 该框架为自主重建复杂的透明对象提供了有效的解决方案.