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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…
cs.CV2024
InstructRL4Pix: Training Diffusion for Image Editing by Reinforcement Learning
Tiancheng Li, Jinxiu Liu, Huajun Chen +1
Instruction-based image editing has made a great process in using natural human language to manipulate the visual content of images. However, existing models are limited by the qua…