Urejanje slik z difuzijskimi modeli na področju mode

Image editing, specifically appearance or style transfer, is an area of computer vision that has seen significant growth due to recent advancements in image diffusion models. There are many different approaches to appearance transfer with fine-tuning, external network adapters and tuning-free methods. In this work, we focus on the latter, where we leverage the existing Stable Diffusion network with some modifications to the internal processing of the attention maps and latent vectors, without modifying the model weights. We propose an appearance transfer method based on partial masking and timestep-controlled appearance modulation, controlling the area and amount of appearance we transfer. The results on the benchmarks outperform current baseline models, which shows the method’s potential for future improvements.