Real Image Editing

Real image editing aims to modify existing photographs using artificial intelligence, primarily leveraging the power of large pre-trained text-to-image diffusion models and generative adversarial networks (GANs). Current research focuses on improving the fidelity of image reconstruction after editing, developing training-free methods to avoid computationally expensive fine-tuning, and enhancing the precision and versatility of edits through techniques like attention mechanisms, noise map guidance, and innovative inversion strategies. These advancements hold significant potential for applications ranging from photo restoration and manipulation to creative content generation and medical imaging.