38 citations · 86 across the 11 of their papers we have counts for
13 papers
Jitter Does Matter: Adapting Gaze Estimation to New Domains
Ruicong Liu, Yiwei Bao, Mingjie Xu +3
Deep neural networks have demonstrated superior performance on appearance-based gaze estimation tasks. However, due to variations in person, illuminations, and background, performa…
Discriminative feature encoding for intrinsic image decomposition
Zongji Wang, Yunfei Liu, Feng Lu
Intrinsic image decomposition is an important and long-standing computer vision problem. Given an input image, recovering the physical scene properties is ill-posed. Several physic…
GazeOnce: Real-Time Multi-Person Gaze Estimation
Mingfang Zhang, Yunfei Liu, Feng Lu
Appearance-based gaze estimation aims to predict the 3D eye gaze direction from a single image. While recent deep learning-based approaches have demonstrated excellent performance,…
Separating Content and Style for Unsupervised Image-to-Image Translation
Yunfei Liu, Haofei Wang, Yang Yue +1
Unsupervised image-to-image translation aims to learn the mapping between two visual domains with unpaired samples. Existing works focus on disentangling domain-invariant content c…
Generalizing Gaze Estimation with Outlier-guided Collaborative Adaptation
Yunfei Liu, Ruicong Liu, Haofei Wang +1
Deep neural networks have significantly improved appearance-based gaze estimation accuracy. However, it still suffers from unsatisfactory performance when generalizing the trained…
Vulnerability of Appearance-based Gaze Estimation
Mingjie Xu, Haofei Wang, Yunfei Liu +1
Appearance-based gaze estimation has achieved significant improvement by using deep learning. However, many deep learning-based methods suffer from the vulnerability property, i.e.…