DICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models
Data Injection and Contrastive Trajectory Refinement is proposed, a training-free inference method that enhances conditional image generation without introducing task-dependent architectures and keeps inference simple while improving cross-task transfer under a unified diffusion formulation.