SOURCE-LINKED INTELLIGENCE
DeCO: Discriminative Evidence Composition for Fine-Grained Dataset Distillation
Dataset distillation compresses a large training set into a compact synthetic set while preserving its downstream utility. However, existing methods primarily preserve global image statistics and may overlook the localized evidence essential for fine-grained visual classification (FGVC), such as object parts, subtle textures, and region-specific structures. We formulate fine-grained dataset distillation as budgeted discriminative-evidence preservation and propose Discriminative Evidence Composition (DeCO). DeCO uses attention rollout from a pretrained TransFG teacher to identify informative pa
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T07:52:27.000Z
First collected: 2026-09-21T09:22:01.459Z. This is not the publication date.