从单目视频进行光照一致的人体-场景重建
Illumination-Consistent Human-Scene Reconstruction from Monocular Video
用可学习光照体（light volume）为人体高斯提供局部光照线索，并用隐式阴影模块分离投射阴影，可直接迁移到单目视频中人体与场景联合重建、重光照与合成任务。
原文依据 a learnable light volume that provides localized lighting cues to human Gaussians
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论从单目视频重建三维人体与场景是一项具有挑战性的任务，其难点主要来自人体运动、变化的光照以及动态场景阴影。尽管近期工作通过联合建模人体与周围场景来探索场景解耦，但它们往往忽略了光照与阴影效应，导致人体外观不一致、场景真实感下降。为弥补这一空白，我们提出基于 3D 高斯泼溅的人体与场景光度一致集成重建，重点建模空间变化的光照与阴影。方法的核心是一个可学习的光照体，它向人体高斯提供局部化的光照线索，从而实现更真实、更一致的外观合成。为进一步保证人体几何与对齐的准确性，我们采用两阶段重建策略：先优化人体网格，再将高斯锚定到细化后的表面。此外，我们引入隐式阴影估计模块，将投射阴影从场景中解耦，从而支持合理的人体阴影合成。该框架还支持人体重光照，以及在具有上下文相宜光照的新场景中进行合成。定量与定性结果均表明，本方法达到最优性能，能够产生一致的外观、真实的光照并提升整体场景真实感。
英文原文摘要 1444 字符
Reconstructing 3D humans and scenes from monocular videos is a challenging task, particularly due to human motion, varying illumination, and dynamic scene shadows. While recent works have explored scene disentanglement by jointly modeling humans and their surrounding scenes, they often overlook illumination and shadow effects--resulting in inconsistent human appearance and degraded scene realism. To address this gap, we propose a photometrically consistent integration of human and scene reconstruction based on 3D Gaussian Splatting, with a key focus on modeling spatially-varying illumination and shadows. Central to our method is a learnable light volume that provides localized lighting cues to human Gaussians, enabling more realistic and consistent appearance synthesis. To further ensure accurate human geometry and alignment, we adopt a two-stage reconstruction strategy: we first optimize a human mesh and then anchor Gaussians to the refined surface. In addition, we introduce an implicit shadow estimation module that disentangles cast shadows from the scene, thus supporting plausible human shadow synthesis. Our framework also facilitates human relighting and compositing into novel scenes with contextually appropriate lighting. Quantitative and qualitative results demonstrate that our method achieves state-of-the-art performance, producing consistent appearances, realistic illumination, and enhanced overall scene realism.