Guiding a pretrained diffusion model toward per-class K-means centroids during sampling improves distilled dataset accuracy on ImageNet subsets by up to 4.4% while avoiding diffusion fine-tuning.
Gener- alized large-scale data condensation via various backbone and statistical matching
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MGD$^3$: Mode-Guided Dataset Distillation using Diffusion Models
Guiding a pretrained diffusion model toward per-class K-means centroids during sampling improves distilled dataset accuracy on ImageNet subsets by up to 4.4% while avoiding diffusion fine-tuning.