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InfoResearchPeer-reviewed
DreamFuse: Toward Realistic and Seamless Image Fusion Across Diverse Scenarios
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Summary
DreamFuse is a unified diffusion-based approach for image fusion that integrates foreground objects into background scenes. The authors curate a cross-scene dataset with iterative in-context learning and existing tools, then use the Diffusion Transformer's attention mechanism to align foreground and background features. The paper reports superiority over state-of-the-art methods across multiple metrics.