activity
20182023
most citedArbitrary Style Transfer via Multi-Adaptation Network

10 citations · 23 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV20221 cited

Draw Your Art Dream: Diverse Digital Art Synthesis with Multimodal Guided Diffusion

Nisha Huang, Fan Tang, Weiming Dong +1

Digital art synthesis is receiving increasing attention in the multimedia community because of engaging the public with art effectively. Current digital art synthesis methods usual…

cs.CV2021

DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis

Shulan Ruan, Yong Zhang, Kun Zhang +4

Text-to-image synthesis refers to generating an image from a given text description, the key goal of which lies in photo realism and semantic consistency. Previous methods usually…

cs.MM2021

Towards Harmonized Regional Style Transfer and Manipulation for Facial Images

Cong Wang, Fan Tang, Yong Zhang +2

Regional facial image synthesis conditioned on semantic mask has achieved great success using generative adversarial networks. However, the appearance of different regions may be i…

cs.CV20218 cited

Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization

Xingjia Pan, Yingguo Gao, Zhiwen Lin +5

Weakly supervised object localization(WSOL) remains an open problem given the deficiency of finding object extent information using a classification network. Although prior works s…

cs.CV2020

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…

cs.CV20203 cited

Distribution Aligned Multimodal and Multi-Domain Image Stylization

Minxuan Lin, Fan Tang, Weiming Dong +3

Multimodal and multi-domain stylization are two important problems in the field of image style transfer. Currently, there are few methods that can perform both multimodal and multi…