Path-space differentiable rendering of participating media

Path-space differentiable rendering of participating media
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参与媒体的路径空间可微渲染

DOI:
10.1145/3450626.3459782
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发表时间:
2021
影响因子:
6.2
通讯作者:
Zhao, Shuang
Zhao, Shuang
中科院分区:
计算机科学1区
文献类型:
--
作者:
Zhang, Cheng;Yu, Zihan;Zhao, Shuang

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基于物理的可微分渲染-其重点是估计辐射检测器响应相对于任意场景参数的导数-具有从解决综合分析问题到训练包含前向渲染过程的机器学习管道的各种应用。不幸的是,现有的通用可微渲染技术要么缺乏处理体积光传输的通用性,要么缺乏设计能够处理复杂几何形状和光传输效应的蒙特卡罗估计器的灵活性。在本文中,我们通过展示如何弥补这一差距广义路径积分可以相对于任意场景参数进行微分。具体来说,我们建立了广义微分路径积分,捕捉界面和体积光传输的数学公式。我们的配方允许先进的微分渲染算法的发展,能够有效地处理具有挑战性的几何不连续性和光传输现象,如体积焦散。我们验证我们的方法,通过比较我们的衍生估计使用有限差分生成的。此外,为了证明我们的技术的有效性,我们比较了微分渲染和逆渲染性能与国家的最先进的方法。
Physics-based differentiable rendering---which focuses on estimating derivatives of radiometric detector responses with respect to arbitrary scene parameters---has a diverse array of applications from solving analysis-by-synthesis problems to training machine-learning pipelines incorporating forward-rendering processes. Unfortunately, existing general-purpose differentiable rendering techniques lack either the generality to handle volumetric light transport or the flexibility to devise Monte Carlo estimators capable of handling complex geometries and light transport effects.In this paper, we bridge this gap by showing how generalized path integrals can be differentiated with respect to arbitrary scene parameters. Specifically, we establish the mathematical formulation of generalized differential path integrals that capture both interfacial and volumetric light transport. Our formulation allows the development of advanced differentiable rendering algorithms capable of efficiently handling challenging geometric discontinuities and light transport phenomena such as volumetric caustics.We validate our method by comparing our derivative estimates to those generated using the finite differences. Further, to demonstrate the effectiveness of our technique, we compare both differentiable rendering and inverse rendering performance with state-of-the-art methods.
蒙特卡罗可微分渲染的对偶采样
DOI: 10.1145/3450626.3459783
发表时间: 2021
影响因子: 6.2
作者:
Zhang, Cheng;Dong, Zhao;Doggett, Michael;Zhao, Shuang
通讯作者: Zhao, Shuang