3 papers
cs.CV2025
Reward-Instruct: A Reward-Centric Approach to Fast Photo-Realistic Image Generation
Yihong Luo, Tianyang Hu, Weijian Luo +2
This paper addresses the challenge of achieving high-quality and fast image generation that aligns with complex human preferences. While recent advancements in diffusion models and…
cs.CV2024
Self-Guidance: Boosting Flow and Diffusion Generation on Their Own
Tiancheng Li, Weijian Luo, Zhiyang Chen +2
Proper guidance strategies are essential to achieve high-quality generation results without retraining diffusion and flow-based text-to-image models. Existing guidance either requi…
cs.CV2024
Schedule On the Fly: Diffusion Time Prediction for Faster and Better Image Generation
Zilyu Ye, Zhiyang Chen, Tiancheng Li +3
Diffusion and flow matching models have achieved remarkable success in text-to-image generation. However, these models typically rely on the predetermined denoising schedules for a…