DMGD achieves better performance than fine-tuned SOTA methods in dataset distillation on ImageNet subsets by using semantic matching through conditional likelihood optimization and OT-based distribution matching in a training-free diffusion setup.
Latent dataset distillation with diffusion models
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A two-stage framework that decouples generation, selection, and refinement to improve budget use in diffusion-based dataset distillation.
D3S2 combines class-balanced mask selection with diffusion-guided image synthesis and two consistency losses to distill 1% datasets that yield 24.99% mIoU on ADE20K and 35.49% on COCO-Stuff, beating random selection.
EDITS improves dataset distillation by fusing VLM-generated textual semantics with image features via Global Semantic Query and Local Semantic Awareness modules, then applying Dual Prototype Guidance with an LLM and diffusion model to synthesize compact datasets.
citing papers explorer
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DMGD: Train-Free Dataset Distillation with Semantic-Distribution Matching in Diffusion Models
DMGD achieves better performance than fine-tuned SOTA methods in dataset distillation on ImageNet subsets by using semantic matching through conditional likelihood optimization and OT-based distribution matching in a training-free diffusion setup.
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Pool-Select-Refine for Allocation-Aware Generative Dataset Distillation
A two-stage framework that decouples generation, selection, and refinement to improve budget use in diffusion-based dataset distillation.
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D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation
D3S2 combines class-balanced mask selection with diffusion-guided image synthesis and two consistency losses to distill 1% datasets that yield 24.99% mIoU on ADE20K and 35.49% on COCO-Stuff, beating random selection.
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EDITS: Enhancing Dataset Distillation with Implicit Textual Semantics
EDITS improves dataset distillation by fusing VLM-generated textual semantics with image features via Global Semantic Query and Local Semantic Awareness modules, then applying Dual Prototype Guidance with an LLM and diffusion model to synthesize compact datasets.