activity
20182022
most citedJoint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

18 citations · 47 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV20221 cited

Semantic-aware One-shot Face Re-enactment with Dense Correspondence Estimation

Yunfan Liu, Qi Li, Zhenan Sun +1

One-shot face re-enactment is a challenging task due to the identity mismatch between source and driving faces. Specifically, the suboptimally disentangled identity information of…

cs.CV20221 cited

GAN-based Facial Attribute Manipulation

Yunfan Liu, Qi Li, Qiyao Deng +2

Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to render desired attributes, which has received significant attention due to its broad practica…

cs.CV202016 cited

Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?

Yunfan Liu, Qi Li, Zhenan Sun +1

Generative Adversarial Networks (GANs) with style-based generators (e.g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed…

cs.CV20205 cited

Reference-guided Face Component Editing

Qiyao Deng, Jie Cao, Yunfan Liu +3

Face portrait editing has achieved great progress in recent years. However, previous methods either 1) operate on pre-defined face attributes, lacking the flexibility of controllin…

cs.CV20196 cited

A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging

Yunfan Liu, Qi Li, Zhenan Sun +1

Face aging, which aims at aesthetically rendering a given face to predict its future appearance, has received significant research attention in recent years. Although great progres…

cs.CV2019

Age Progression and Regression with Spatial Attention Modules

Qi Li, Yunfan Liu, Zhenan Sun

Age progression and regression refers to aesthetically render-ing a given face image to present effects of face aging and rejuvenation, respectively. Although numerous studies have…