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Antithetic Sampling for Monte Carlo Differentiable Rendering

delete2021-07-19
delete17
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OA
AI
C
Cheng Zhang *
Z
Zhao Yang Dong
M
Michael Doggett
S
Shuang Zhao
DOI:10.1145/3450626.3459783delete
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摘要

摘要

En 中文
Stochastic sampling of light transport paths is key to Monte Carlo forward rendering, and previous studies have led to mature techniques capable of drawing high-contribution light paths in complex scenes. These sampling techniques have also been applied to differentiable rendering. In this paper, we demonstrate that path sampling techniques developed for forward rendering can become inefficient for differentiable rendering of glossy materials-especially when estimating derivatives with respect to global scene geometries. To address this problem, we introduce antithetic sampling of BSDFs and light-transport paths, allowing significantly faster convergence and can be easily integrated into existing differentiable rendering pipelines. We validate our method by comparing our derivative estimates to those generated with existing unbiased techniques. Further, we demonstrate the effectiveness of our technique by providing equal-quality and equal-time comparisons with existing sampling methods.
Keyword:
Differentiable rendering
antithetic sampling
glossy materials
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期刊

ACM Transactions on Graphics 封面图
ACM Transactions on Graphics
IF:
9.5
论文数:
4.7K
被引数:
3.6W

机构

University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
U
university of california irvine
学者数:
2.3W
论文数: 1.7W
被引数: 55
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