Large Vision-Language Models (LVLMs) combine computer vision and natural language processing to generate text descriptions of visual content. These models have shown remarkable progress in various applications, including image captioning, visible question answering, and image retrieval. However, despite their impressive performance, LVLMs still face some challenges, particularly when it comes to specialized tasks that require…

Diffusion models have shown to be very successful in producing high-quality photographs when given text suggestions. This paradigm for Text-to-picture (T2I) production has been successfully used for several downstream applications, including depth-driven picture generation and subject/segmentation identification. Two popular text-conditioned diffusion models, CLIP models and Latent Diffusion Models (LDM), often called Stable Diffusion, are essential…