210 citations · 587 across the 34 of their papers we have counts for
8 papers · 1 filter
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…
Unsupervised Pre-training for Person Re-identification
Dengpan Fu, Dongdong Chen, Jianmin Bao +5
In this paper, we present a large scale unlabeled person re-identification (Re-ID) dataset "LUPerson" and make the first attempt of performing unsupervised pre-training for improvi…
A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint
Weijian Huang, Hao Yang, Xinfeng Liu +5
Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless,…
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation
Adit Krishnan, Mahashweta Das, Mangesh Bendre +2
The rapid proliferation of new users and items on the social web has aggravated the gray-sheep user/long-tail item challenge in recommender systems. Historically, cross-domain co-c…
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…
Feedback Graph Convolutional Network for Skeleton-based Action Recognition
Hao Yang, Dan Yan, Li Zhang +4
Skeleton-based action recognition has attracted considerable attention in computer vision since skeleton data is more robust to the dynamic circumstance and complicated background…
Multi-Task Incremental Learning for Object Detection
Xialei Liu, Hao Yang, Avinash Ravichandran +2
Multi-task learns multiple tasks, while sharing knowledge and computation among them. However, it suffers from catastrophic forgetting of previous knowledge when learned incrementa…
Eco-Driving at Signalized Intersections: A Multiple Signal Optimization Approach
Hao Yang, Fawaz Almutairi, Hesham A. Rakha
Consecutive traffic signalized intersections can increase vehicle stops, producing vehicle accelerations on arterial roads and potentially increasing vehicle fuel consumption level…