34 citations · 55 across the 10 of their papers we have counts for
11 papers
Sissi: Zero-shot Style-guided Image Synthesis via Semantic-style Integration
Yingying Deng, Xiangyu He, Fan Tang +2
Text-guided image generation has advanced rapidly with large-scale diffusion models, yet achieving precise stylization with visual exemplars remains difficult. Existing approaches…
Inversion-Free Style Transfer with Dual Rectified Flows
Yingying Deng, Xiangyu He, Fan Tang +2
Style transfer, a pivotal task in image processing, synthesizes visually compelling images by seamlessly blending realistic content with artistic styles, enabling applications in p…
Multi-turn Consistent Image Editing
Zijun Zhou, Yingying Deng, Xiangyu He +2
Many real-world applications, such as interactive photo retouching, artistic content creation, and product design, require flexible and iterative image editing. However, existing i…
Z-Magic: Zero-shot Multiple Attributes Guided Image Creator
Yingying Deng, Xiangyu He, Fan Tang +1
The customization of multiple attributes has gained popularity with the rising demand for personalized content creation. Despite promising empirical results, the contextual coheren…
FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
Yingying Deng, Xiangyu He, Changwang Mei +2
Though Rectified Flows (ReFlows) with distillation offers a promising way for fast sampling, its fast inversion transforms images back to structured noise for recovery and followin…
Z-STAR+: A Zero-shot Style Transfer Method via Adjusting Style Distribution
Yingying Deng, Xiangyu He, Fan Tang +1
Style transfer presents a significant challenge, primarily centered on identifying an appropriate style representation. Conventional methods employ style loss, derived from second-…
: Zero-shot Style Transfer via Attention Rearrangement
Yingying Deng, Xiangyu He, Fan Tang +1
Despite the remarkable progress in image style transfer, formulating style in the context of art is inherently subjective and challenging. In contrast to existing learning/tuning m…
StyTr: Image Style Transfer with Transformers
Yingying Deng, Fan Tang, Weiming Dong +4
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 convoluti…
Arbitrary Video Style Transfer via Multi-Channel Correlation
Yingying Deng, Fan Tang, Weiming Dong +3
Video style transfer is getting more attention in AI community for its numerous applications such as augmented reality and animation productions. Compared with traditional image st…
Arbitrary Style Transfer via Multi-Adaptation Network
Yingying Deng, Fan Tang, Weiming Dong +3
Arbitrary style transfer is a significant topic with research value and application prospect. A desired style transfer, given a content image and referenced style painting, would r…
Multi-Attribute Guided Painting Generation
Minxuan Lin, Yingying Deng, Fan Tang +2
Controllable painting generation plays a pivotal role in image stylization. Currently, the control way of style transfer is subject to exemplar-based reference or a random one-hot…