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LightOctree: Lightweight 3D Spatially-Coherent Indoor Lighting Estimation

  • Xuecan Wang
  • , Shibang Xiao
  • , Xiaohui Liang*
  • *此作品的通讯作者
  • Beihang University
  • Zhongguancun Laboratory

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

We present a lightweight solution for estimating spatially-coherent indoor lighting from a single RGB image. Previous methods for estimating illumination using volumetric repre-sentations have overlooked the sparse distribution of light sources in space, necessitating substantial memory and computational resources for achieving high-quality results. We introduce a unified, voxel octree-based illumination estimation framework to produce 3D spatially-coherent lighting. Additionally, a differentiable voxel octree cone tracing ren-dering layer is proposed to eliminate regular volumetric representation throughout the entire process and ensure the retention of features across different frequency domains. This reduction significantly decreases spatial usage and required floating-point operations without substantially compromising precision. Experimental results demonstrate that our approach achieves high-quality coherent estimation with minimal cost compared to previous methods.

源语言英语
主期刊名Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
出版商IEEE Computer Society
页4536-4545
页数10
ISBN(电子版)9798350353006
DOI
出版状态已出版 - 2024
活动2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 - Seattle, 美国
期限: 16 6月 2024 → 22 6月 2024

丛书

姓名Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN(印刷版)1063-6919

会议

会议2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024
国家/地区美国
市Seattle
时期16/06/24 → 22/06/24

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