Image data augmentation constitutes a critical methodology in modern computer vision
tasks, since it can facilitate towards enhancing the diversity and quality of training datasets; …

Personalization is an important topic in text-to-image generation, especially the challenging
multi-concept personalization. Current multi-concept methods are struggling with identity …

Image stylization involves manipulating the visual appearance and texture (style) of an
image while preserving its underlying objects, structures, and concepts (content). The …

Recent advances in text-to-image generation models have unlocked vast potential for visual
creativity. However, the users that use these models struggle with the generation of …

We propose Magic Clothing, a latent diffusion model (LDM)-based network architecture for
an unexplored garment-driven image synthesis task. Aiming at generating customized …

Visually oriented designers often struggle to create effective generative AI (GenAI) prompts.
A preliminary study identified specific issues in composing and fine-tuning prompts, as well …

Recent text-to-image generative models have enabled us to transform our words into
vibrant, captivating imagery. The surge of personalization techniques that has followed has …

Content creators often aim to create personalized images using personal subjects that go
beyond the capabilities of conventional text-to-image models. Additionally, they may want …

Abstract Text-to-Image (T2I) generation has made significant advancements with the advent
of diffusion models. These models exhibit remarkable abilities to produce images based on …

Creativity serves as a cornerstone for societal progress and innovation. With the rise of
advanced generative AI models capable of tasks once reserved for human creativity, the …