A Simple Approach to Differentiable Rendering of SDFs
<|reference_start|>A Simple Approach to Differentiable Rendering of SDFs: We present a simple algorithm for differentiable rendering of surfaces represented by Signed Distance Fields (SDF), which makes it easy to integrate rendering into gradient-based optimization pipelines. To tackle visibility-related derivatives that make rendering non-differentiable, existing physically based differentiable rendering methods often rely on elaborate guiding data structures or reparameterization with a global impact on variance. In this article, we investigate an alternative that embraces nonzero bias in exchange for low variance and architectural simplicity. Our method expands the lower-dimensional boundary integral into a thin band that is easy to sample when the underlying surface is represented by an SDF. We demonstrate the performance and robustness of our formulation in end-to-end inverse rendering tasks, where it obtains results that are competitive with or superior to existing work.<|reference_end|>
@article{wang2024a,
    title={A Simple Approach to Differentiable Rendering of SDFs},
    author={Zichen Wang, Xi Deng, Ziyi Zhang, Wenzel Jakob, Steve Marschner},
    journal={arXiv preprint arXiv:2405.08733},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.08733},
    primaryClass={cs.GR cs.CV}
}