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HEADHUNTER: Training-Free Annotated Dataset Synthesis via Self-Guided Diffusion Transformer Attention Head Selection

2026-07-01

Abstract excerpt

Pixel-level annotation remains a major bottleneck for semantic segmentation, motivating methods that synthesize image-label pairs directly from generative models. Prior synthetic dataset generators typically obtain pseudo-labels from cross-attention maps or learned decoders over generative features; however, recent text-to-image (T2I) models increasingly use multimodal diffusion transformers (MM-DiTs), where conce...

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Radiomics and Machine Learning in Medical Imaging

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Literature Corpus work: 27463918-b9f2-5f66-9c8d-d7f5b4d2011b
DOI: 10.20944/preprints202606.2132.v2

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