Contrastive Adapter Training for Preserving Model Knowledge in Personalized Image Generation

Contrastive Adapter Training (CAT) is a simple yet effective strategy to enhance adapter training in diffusion models, facilitating the preservation of the base model's original knowledge when initiating adapters for personalized image generation.