The field of image generation is moving towards greater controllability and realism, with a focus on fine-grained manipulation of objects, scenes, and attributes. Recent developments have enabled the generation of high-quality images with precise control over pose, size, orientation, and other factors. This has significant implications for applications such as e-commerce, surveillance, and design. Notably, innovative methods have been proposed to address challenges such as garment deformation, texture distortion, and limited controllability. These advancements have the potential to revolutionize the field and enable new use cases. Noteworthy papers include: FashionMAC, which achieves deformation-free fashion image generation with fine-grained model appearance customization. Physically Realistic Sequence-Level Adversarial Clothing generates natural, printable adversarial textures for shirts, trousers, and hats that remain effective throughout entire walking videos. Controllable Layer Decomposition enables fine-grained and controllable multi-layer separation of raster images. SceneDesigner allows for controllable multi-object image generation with 9-DoF pose manipulation.