用物理可微渲染解决逆问题，提升三维场景重建精度
Physics Based Differentiable Rendering for Inverse Problems and Beyond
- 基于物理光传播与材质交互建模，实现图像到几何/材质的反向推导
- 在自动驾驶、场景重建等任务中显著提升属性还原准确率
- 适合计算机视觉、图形学及逆问题研究者参考
基于物理的可微渲染（PBDR）已成为计算机视觉、图形学和机器学习中解决各类逆问题的高效方法。通过引入光传播与材料相互作用的物理模型，PBDR能够从感知数据生成对象的几何、材质和光照等属性。得益于这一能力，该技术已被广泛应用于自动驾驶、场景重建和材料设计等领域。本文系统综述了PBDR技术的发展脉络，重点分析其构建原理、实际效果与局限性，并探讨其在现实场景中的应用价值。
原文摘要 · Abstract (English)
Physics-based differentiable rendering (PBDR) has become an efficient method in computer vision, graphics, and machine learning for addressing an array of inverse problems. PBDR allows patterns to be generated from perceptions which can be applied to enhance object attributes like geometry, substances, and lighting by adding physical models of light propagation and materials interaction. Due to these capabilities, distinguished rendering has been employed in a wider range of sectors such as autonomous navigation, scene reconstruction, and material design. We provide an extensive overview of PBDR techniques in this study, emphasizing their creation, effectiveness, and limitations while managing inverse situations. We demonstrate modern techniques and examine their value in everyday situations.
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