Spherical Voronoi: Directional Appearance as a Differentiable Partition of the Sphere
Analysis
This article likely presents a novel approach to representing and manipulating directional data using a differentiable Voronoi diagram on a sphere. The focus is on creating a partition of the sphere that allows for the modeling of appearance based on direction. The use of 'differentiable' suggests the method is designed to be integrated into machine learning pipelines, enabling gradient-based optimization.
Key Takeaways
Reference
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