Path-Space Differentiable Rendering of Implicit Surfaces
Siwei Zhou, Youngha Chang, Nobuhiko Mukai, Hiroaki Santo, Fumio Okura, Yasuyuki Matsushita, Shuang Zhao
Abstract
Physics-based differentiable rendering is a key ingredient for integrating forward rendering into probabilistic inference and machine learning pipelines. As a state-of-the-art formulation for differentiable rendering, differential path integrals have enabled the development of efficient Monte Carlo estimators for both interior and boundary integrals. Unfortunately, this formulation has been designed mostly for explicit geometries like polygonal meshes.
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