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cs.CV2025
HPSv3: Towards Wide-Spectrum Human Preference Score
Yuhang Ma, Yunhao Shui, Xiaoshi Wu +2
Evaluating text-to-image generation models requires alignment with human perception, yet existing human-centric metrics are constrained by limited data coverage, suboptimal feature…
cs.CV2024
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
Dongzhi Jiang, Guanglu Song, Xiaoshi Wu +5
Diffusion models have demonstrated great success in the field of text-to-image generation. However, alleviating the misalignment between the text prompts and images is still challe…
cs.CV2024
Deep Reward Supervisions for Tuning Text-to-Image Diffusion Models
Xiaoshi Wu, Yiming Hao, Manyuan Zhang +5
Optimizing a text-to-image diffusion model with a given reward function is an important but underexplored research area. In this study, we propose Deep Reward Tuning (DRTune), an a…