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We propose a point generation method to handle anisotropic distributions by example. We use the Pair-Correlation Function (PCF) to compute distance distributions along multiple directions. Our method can handle a wider range of exemplar distributions than previous example-based methods, and is competitive with neural methods for quality while outperforming them in synthesis speed.

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Anisotropic Point Synthesis by Example

  • 会议论文

  • 发表日期：

    2025年

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  • Brian Yang,
  • David Mould

摘要

We propose a point generation method to handle anisotropic distributions by example. We use the Pair-Correlation Function (PCF) to compute distance distributions along multiple directions. Our method can handle a wider range of exemplar distributions than previous example-based methods, and is competitive with neural methods for quality while outperforming them in synthesis speed.