SGD-Mix combines saliency-guided foreground/background mixing with a fine-tuned diffusion model to create label-preserving augmented images, reporting modest accuracy gains over Diff-Mix across four classification benchmark families.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation
SGD-Mix combines saliency-guided foreground/background mixing with a fine-tuned diffusion model to create label-preserving augmented images, reporting modest accuracy gains over Diff-Mix across four classification benchmark families.