4 papers
Lay2Story: Extending Diffusion Transformers for Layout-Togglable Story Generation
Ao Ma, Jiasong Feng, Ke Cao +4
Storytelling tasks involving generating consistent subjects have gained significant attention recently. However, existing methods, whether training-free or training-based, continue…
SPAST: Arbitrary Style Transfer with Style Priors via Pre-trained Large-scale Model
Zhanjie Zhang, Quanwei Zhang, Junsheng Luan +3
Given an arbitrary content and style image, arbitrary style transfer aims to render a new stylized image which preserves the content image's structure and possesses the style image…
RAGAR: Retrieval Augmented Personalized Image Generation Guided by Recommendation
Run Ling, Wenji Wang, Yuting Liu +12
Personalized image generation is crucial for improving the user experience, as it renders reference images into preferred ones according to user visual preferences. Although effect…
DyArtbank: Diverse Artistic Style Transfer via Pre-trained Stable Diffusion and Dynamic Style Prompt Artbank
Zhanjie Zhang, Quanwei Zhang, Guangyuan Li +4
Artistic style transfer aims to transfer the learned style onto an arbitrary content image. However, most existing style transfer methods can only render consistent artistic styliz…