103 citations · 140 across the 10 of their papers we have counts for
10 papers
SMARTQUERY: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction
Xiaoting Li, Yuhang Wu, Vineeth Rakesh +3
Graph neural networks have achieved significant success in representation learning. However, the performance gains come at a cost; acquiring comprehensive labeled data for training…
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID
Yuhang Wu, Tengteng Huang, Haotian Yao +5
Recently, many approaches tackle the Unsupervised Domain Adaptive person re-identification (UDA re-ID) problem through pseudo-label-based contrastive learning. During training, a u…
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection
Yuhang Wu, Mengting Gu, Lan Wang +3
Modeling inter-dependencies between time-series is the key to achieve high performance in anomaly detection for multivariate time-series data. The de-facto solution to model the de…
Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions
Yuhang Wu, Sunpreet S. Arora, Yanhong Wu +1
Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers. State-of-the-art adversarial example detection methods characterize a…
GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation
Aravind Sankar, Yanhong Wu, Yuhang Wu +3
We study the problem of making item recommendations to ephemeral groups, which comprise users with limited or no historical activities together. Existing studies target persistent…
Adversarial Light Projection Attacks on Face Recognition Systems: A Feasibility Study
Dinh-Luan Nguyen, Sunpreet S. Arora, Yuhang Wu +1
Deep learning-based systems have been shown to be vulnerable to adversarial attacks in both digital and physical domains. While feasible, digital attacks have limited applicability…
Occlusion-guided compact template learning for ensemble deep network-based pose-invariant face recognition
Yuhang Wu, Ioannis A. Kakadiaris
Concatenation of the deep network representations extracted from different facial patches helps to improve face recognition performance. However, the concatenated facial template i…
Convolutional Point-set Representation: A Convolutional Bridge Between a Densely Annotated Image and 3D Face Alignment
Yuhang Wu, Le Anh Vu Ha, Xiang Xu +1
We present a robust method for estimating the facial pose and shape information from a densely annotated facial image. The method relies on Convolutional Point-set Representation (…
Facial 3D Model Registration Under Occlusions With SensiblePoints-based Reinforced Hypothesis Refinement
Yuhang Wu, Ioannis A. Kakadiaris
Registering a 3D facial model to a 2D image under occlusion is difficult. First, not all of the detected facial landmarks are accurate under occlusions. Second, the number of relia…
GoDP: Globally optimized dual pathway system for facial landmark localization in-the-wild
Yuhang Wu, Shishir K. Shah, Ioannis A. Kakadiaris
Facial landmark localization is a fundamental module for pose-invariant face recognition. The most common approach for facial landmark detection is cascaded regression, which is co…