Layout to Image

Layout-to-image (L2I) generation aims to synthesize realistic images guided by predefined layouts, addressing the limitations of text-to-image models in precise spatial control. Current research focuses on improving the accuracy and fidelity of generated instances within these layouts, often employing diffusion models enhanced with modules like cross-attention mechanisms and adversarial training to refine object placement and features. This field is significant for advancing controllable image generation, impacting applications such as image editing, video generation, and data augmentation for computer vision tasks.