A CLIP-aligned, diffusion-generated 'low-biased' ImageNet improves backbone pre-training transfer accuracy and reduces shape, context, and background biases relative to real ImageNet and earlier synthetic datasets.
Food-101–mining discriminative components with random forests
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Low-Biased General Annotated Dataset Generation
A CLIP-aligned, diffusion-generated 'low-biased' ImageNet improves backbone pre-training transfer accuracy and reduces shape, context, and background biases relative to real ImageNet and earlier synthetic datasets.