One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation

Apple researchers have developed a method to integrate pretrained visual encoders into image generation models by adding only a single layer of trainable parameters. This approach allows generative models to leverage existing high-quality image representations without the computational overhead of retraining large architectures from scratch. By bridging the gap between discriminative encoders and generative decoders, this technique improves efficiency and output quality for latent diffusion models.