collaborators

5 papers

cs.CV2026

HiFi-Inpaint: Towards High-Fidelity Reference-Based Inpainting for Generating Detail-Preserving Human-Product Images

Yichen Liu, Donghao Zhou, Jie Wang +9

Human-product images, which showcase the integration of humans and products, play a vital role in advertising, e-commerce, and digital marketing. The essential challenge of generat…

cs.IR2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…