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cs.CV2025
MUSE: Multi-Subject Unified Synthesis via Explicit Layout Semantic Expansion
Fei Peng, Junqiang Wu, Yan Li +3
Existing text-to-image diffusion models have demonstrated remarkable capabilities in generating high-quality images guided by textual prompts. However, achieving multi-subject comp…
cs.CV2024
Learning Multi-dimensional Human Preference for Text-to-Image Generation
Sixian Zhang, Bohan Wang, Junqiang Wu +4
Current metrics for text-to-image models typically rely on statistical metrics which inadequately represent the real preference of humans. Although recent work attempts to learn th…