111 citations · 134 across the 16 of their papers we have counts for
16 papers
Learning Expressive And Generalizable Motion Features For Face Forgery Detection
Jingyi Zhang, Peng Zhang, Jingjing Wang +2
Previous face forgery detection methods mainly focus on appearance features, which may be easily attacked by sophisticated manipulation. Considering the majority of current face ma…
Single Domain Dynamic Generalization for Iris Presentation Attack Detection
Yachun Li, Jingjing Wang, Yuhui Chen +2
Iris presentation attack detection (PAD) has achieved great success under intra-domain settings but easily degrades on unseen domains. Conventional domain generalization methods mi…
Rethinking the Approximation Error in 3D Surface Fitting for Point Cloud Normal Estimation
Hang Du, Xuejun Yan, Jingjing Wang +2
Most existing approaches for point cloud normal estimation aim to locally fit a geometric surface and calculate the normal from the fitted surface. Recently, learning-based methods…
NeRF-Gaze: A Head-Eye Redirection Parametric Model for Gaze Estimation
Pengwei Yin, Jiawu Dai, Jingjing Wang +2
Gaze estimation is the fundamental basis for many visual tasks. Yet, the high cost of acquiring gaze datasets with 3D annotations hinders the optimization and application of gaze e…
FBNet: Feedback Network for Point Cloud Completion
Xuejun Yan, Hongyu Yan, Jingjing Wang +5
The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedfo…
Point Cloud Upsampling via Cascaded Refinement Network
Hang Du, Xuejun Yan, Jingjing Wang +2
Point cloud upsampling focuses on generating a dense, uniform and proximity-to-surface point set. Most previous approaches accomplish these objectives by carefully designing a sing…
Multi-Scale Wavelet Transformer for Face Forgery Detection
Jie Liu, Jingjing Wang, Peng Zhang +3
Currently, many face forgery detection methods aggregate spatial and frequency features to enhance the generalization ability and gain promising performance under the cross-dataset…
Semi-supervised Ranking for Object Image Blur Assessment
Qiang Li, Zhaoliang Yao, Jingjing Wang +4
Assessing the blurriness of an object image is fundamentally important to improve the performance for object recognition and retrieval. The main challenge lies in the lack of abund…
Weakly Supervised Regional and Temporal Learning for Facial Action Unit Recognition
Jingwei Yan, Jingjing Wang, Qiang Li +2
Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations. To alleviate this problem, a large amount of efforts has been dedicat…
Few-shot One-class Domain Adaptation Based on Frequency for Iris Presentation Attack Detection
Yachun Li, Ying Lian, Jingjing Wang +3
Iris presentation attack detection (PAD) has achieved remarkable success to ensure the reliability and security of iris recognition systems. Most existing methods exploit discrimin…
Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression
Qiang Li, Jingjing Wang, Zhaoliang Yao +5
Learning from a label distribution has achieved promising results on ordinal regression tasks such as facial age and head pose estimation wherein, the concept of adaptive label dis…
Learning Multiple Explainable and Generalizable Cues for Face Anti-spoofing
Ying Bian, Peng Zhang, Jingjing Wang +2
Although previous CNN based face anti-spoofing methods have achieved promising performance under intra-dataset testing, they suffer from poor generalization under cross-dataset tes…
Self-Supervised Regional and Temporal Auxiliary Tasks for Facial Action Unit Recognition
Jingwei Yan, Jingjing Wang, Qiang Li +2
Automatic facial action unit (AU) recognition is a challenging task due to the scarcity of manual annotations. To alleviate this problem, a large amount of efforts has been dedicat…
Multi-Level Adaptive Region of Interest and Graph Learning for Facial Action Unit Recognition
Jingwei Yan, Boyuan Jiang, Jingjing Wang +3
In facial action unit (AU) recognition tasks, regional feature learning and AU relation modeling are two effective aspects which are worth exploring. However, the limited represent…
Self-Domain Adaptation for Face Anti-Spoofing
Jingjing Wang, Jingyi Zhang, Ying Bian +3
Although current face anti-spoofing methods achieve promising results under intra-dataset testing, they suffer from poor generalization to unseen attacks. Most existing works adopt…
Constructing a Non-Negative Low Rank and Sparse Graph with Data-Adaptive Features
Liansheng Zhuang, Shenghua Gao, Jinhui Tang +3
This paper aims at constructing a good graph for discovering intrinsic data structures in a semi-supervised learning setting. Firstly, we propose to build a non-negative low-rank a…