Diversified Semantic Distribution Matching for Dataset Distillation

Hongcheng Li, Yucan Zhou, Xiaoyan Gu, Bo Li, Weiping Wang

MM 2024 · first public 2024-10

paper ↗code ↗catalogued✓ abstract read

In one paragraph

Matches both class-wise Gaussian prototypes and covariance matrices of pretrained-model features between real and synthetic data, rather than means alone, to increase within-class diversity of the distilled set, reporting state-of-the-art distribution-matching results on both image and speech datasets.

Where it sits

Distribution and feature matching (Surrogate matching)
Setting: Image classification
Setting: Other data types

Builds on

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DEDA

BibTeX (generated; prefer the venue's official entry)

@article{li2024diversified,
  title   = {Diversified Semantic Distribution Matching for Dataset Distillation},
  author  = {Hongcheng Li and Yucan Zhou and Xiaoyan Gu and Bo Li and Weiping Wang},
  journal = {MM 2024},
  year    = {2024}
}

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