A prompt-free conditional diffusion framework with a detector-based counting loss augments multi-object images with matched per-category object counts and diverse layouts, achieving the best downstream COCO detection mAP among compared baselines (39.04 vs 38.65 without augmentation).
Make it count: Text-to-image generation with an accurate number of objects, 2024
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Prompt-Free Conditional Diffusion for Multi-object Image Augmentation
A prompt-free conditional diffusion framework with a detector-based counting loss augments multi-object images with matched per-category object counts and diverse layouts, achieving the best downstream COCO detection mAP among compared baselines (39.04 vs 38.65 without augmentation).