3 papers
cs.CV2026
RADIANCE: Relative Adaptive Denoising with IP-Adapter for Novel Concept Enhancement
Zi-Xiang Ni, Bo-Lun Huang, Teng-Fang Hsiao +2
Text-to-image (T2I) diffusion models have achieved striking progress but still struggle to synthesize rare concepts involving unusual attribute-object pairings, often resulting in…
cs.CV2025
Color Me Correctly: Bridging Perceptual Color Spaces and Text Embeddings for Improved Diffusion Generation
Sung-Lin Tsai, Bo-Lun Huang, Yu Ting Shen +5
Accurate color alignment in text-to-image (T2I) generation is critical for applications such as fashion, product visualization, and interior design, yet current diffusion models st…
cs.CV2025
Score Replacement with Bounded Deviation for Rare Prompt Generation
Bo-Kai Ruan, Zi-Xiang Ni, Bo-Lun Huang +2
Diffusion models achieve impressive performance in high-fidelity image generation but often struggle with rare concepts that appear infrequently in the training distribution. Prior…