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- W4310562506 abstract "Current differentiable renderers provide light transport gradients with respect to arbitrary scene parameters. However, the mere existence of these gradients does not guarantee useful update steps in an optimization. Instead, inverse rendering might not converge due to inherent plateaus, i.e., regions of zero gradient, in the objective function. We propose to alleviate this by convolving the high-dimensional rendering function that maps scene parameters to images with an additional kernel that blurs the parameter space. We describe two Monte Carlo estimators to compute plateau-free gradients efficiently, i.e., with low variance, and show that these translate into net-gains in optimization error and runtime performance. Our approach is a straightforward extension to both black-box and differentiable renderers and enables optimization of problems with intricate light transport, such as caustics or global illumination, that existing differentiable renderers do not converge on." @default.
- W4310562506 created "2022-12-12" @default.
- W4310562506 creator A5045018128 @default.
- W4310562506 creator A5084442493 @default.
- W4310562506 date "2022-11-30" @default.
- W4310562506 modified "2023-10-18" @default.
- W4310562506 title "Plateau-reduced Differentiable Path Tracing" @default.
- W4310562506 doi "https://doi.org/10.48550/arxiv.2211.17263" @default.
- W4310562506 hasPublicationYear "2022" @default.
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