Approximate Differentiable Rendering with Algebraic Surfaces
نویسندگان
چکیده
Differentiable renderers provide a direct mathematical link between an object’s 3D representation and images of that object. In this work, we develop approximate differentiable renderer for compact, interpretable representation, which call Fuzzy Metaballs. Our focuses on rendering shapes via depth maps silhouettes. It sacrifices fidelity utility, producing fast runtimes high-quality gradient information can be used to solve vision tasks. Compared mesh-based renderers, our method has forward passes are 5x faster backwards 30x faster. The silhouette generated by smooth defined everywhere. evaluation pose estimation, show is the only one comparable classic techniques. shape from silhouette, performs well using descent per-pixel loss, without any surrogate losses or regularization. These reconstructions work even natural video sequences with segmentation artifacts. Project page: https://leonidk.github.io/fuzzy-metaballs
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ژورنال
عنوان ژورنال: Lecture Notes in Computer Science
سال: 2022
ISSN: ['1611-3349', '0302-9743']
DOI: https://doi.org/10.1007/978-3-031-19824-3_35