6 accepted papers
Though Rectified Flows (ReFlows) with distillation offer a promising way for fast sampling, its fast inversion transforms images back to structured noise for recovery and following editing remains unsolved. This paper introduces FireFlow, an embarrassingly simple yet effective zero-shot approach tha…
Many real-world applications, such as interactive photo retouching, artistic content creation, and product design, require flexible and iterative image editing. However, existing image editing methods primarily focus on achieving the desired modifications in a single step, which often struggles with…
We concentrate on a novel human-centric image synthesis task that is given only one reference facial photograph it is expected to generate specific individual images with diverse head positions poses facial expressions and illuminations in different contexts. To accomplish this goal we argue that ou…
Despite the remarkable progress in image style transfer formulating style in the context of art is inherently subjective and challenging. In contrast to existing methods this study shows that vanilla diffusion models can directly extract style information and seamlessly integrate the generative prio…
The goal of image style transfer is to render an image with artistic features guided by a style reference while maintaining the original content. Owing to the locality in convolutional neural networks (CNNs), extracting and maintaining the global information of input images is difficult. Therefore,…
Video style transfer is attracting increasing attention from the artificial intelligence community because of its numerous applications, such as augmented reality and animation production. Relative to traditional image style transfer, video style transfer presents new challenges, including how to ef…