A new 100k triplet dataset and in-context diffusion framework ICTone enable state-of-the-art tone style transfer by jointly conditioning on content and reference images with scorer-based reward learning.
arXiv preprint arXiv:2507.01926 (2025)
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PostureObjectStitch generates assembly-aware anomaly images by decoupling multi-view features into high-frequency, texture and RGB components, modulating them temporally in a diffusion model, and applying conditional loss plus geometric priors to preserve correct component relationships.
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Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset
A new 100k triplet dataset and in-context diffusion framework ICTone enable state-of-the-art tone style transfer by jointly conditioning on content and reference images with scorer-based reward learning.
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PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios
PostureObjectStitch generates assembly-aware anomaly images by decoupling multi-view features into high-frequency, texture and RGB components, modulating them temporally in a diffusion model, and applying conditional loss plus geometric priors to preserve correct component relationships.