24 citations · 47 across the 20 of their papers we have counts for
20 papers · 1 filter
DBLFace: Domain-Based Labels for NIR-VIS Heterogeneous Face Recognition
Ha Le, Ioannis A. Kakadiaris
Deep learning-based domain-invariant feature learning methods are advancing in near-infrared and visible (NIR-VIS) heterogeneous face recognition. However, these methods are prone…
On Improving the Generalization of Face Recognition in the Presence of Occlusions
Xiang Xu, Nikolaos Sarafianos, Ioannis A. Kakadiaris
In this paper, we address a key limitation of existing 2D face recognition methods: robustness to occlusions. To accomplish this task, we systematically analyzed the impact of faci…
Adversarial Representation Learning for Text-to-Image Matching
Nikolaos Sarafianos, Xiang Xu, Ioannis A. Kakadiaris
For many computer vision applications such as image captioning, visual question answering, and person search, learning discriminative feature representations at both image and text…
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…
Open Source Face Recognition Performance Evaluation Package
Xiang Xu, Ioannis A. Kakadiaris
Biometrics-related research has been accelerated significantly by deep learning technology. However, there are limited open-source resources to help researchers evaluate their deep…
Deep Imbalanced Attribute Classification using Visual Attention Aggregation
Nikolaos Sarafianos, Xiang Xu, Ioannis A. Kakadiaris
For many computer vision applications, such as image description and human identification, recognizing the visual attributes of humans is an essential yet challenging problem. Its…
Fully Associative Patch-based 1-to-N Matcher for Face Recognition
Lingfeng Zhang, Ioannis A. Kakadiaris
This paper focuses on improving face recognition performance by a patch-based 1-to-N signature matcher that learns correlations between different facial patches. A Fully Associativ…
A Hierarchical Matcher using Local Classifier Chains
Lingfeng Zhang, Ioannis A. Kakadiaris
This paper focuses on improving the performance of current convolutional neural networks in visual recognition without changing the network architecture. A hierarchical matcher is…
Patch-based Face Recognition using a Hierarchical Multi-label Matcher
Lingfeng Zhang, Pengfei Dou, Ioannis A Kakadiaris
This paper proposes a hierarchical multi-label matcher for patch-based face recognition. In signature generation, a face image is iteratively divided into multi-level patches. Two…
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 (…
A Face Recognition Signature Combining Patch-based Features with Soft Facial Attributes
Lingfeng Zhang, Pengfei Dou, Ioannis A. Kakadiaris
This paper focuses on improving face recognition performance with a new signature combining implicit facial features with explicit soft facial attributes. This signature has two co…
When 3D-Aided 2D Face Recognition Meets Deep Learning: An extended UR2D for Pose-Invariant Face Recognition
Xiang Xu, Pengfei Dou, Ha A. Le +1
Most of the face recognition works focus on specific modules or demonstrate a research idea. This paper presents a pose-invariant 3D-aided 2D face recognition system (UR2D) that is…
Human Activity Recognition Using Robust Adaptive Privileged Probabilistic Learning
Michalis Vrigkas, Evangelos Kazakos, Christophoros Nikou +1
In this work, a novel method based on the learning using privileged information (LUPI) paradigm for recognizing complex human activities is proposed that handles missing informatio…
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…
Curriculum Learning of Visual Attribute Clusters for Multi-Task Classification
Nikolaos Sarafianos, Theodore Giannakopoulos, Christophoros Nikou +1
Visual attributes, from simple objects (e.g., backpacks, hats) to soft-biometrics (e.g., gender, height, clothing) have proven to be a powerful representational approach for many a…
Inferring Human Activities Using Robust Privileged Probabilistic Learning
Michalis Vrigkas, Evangelos Kazakos, Christophoros Nikou +1
Classification models may often suffer from "structure imbalance" between training and testing data that may occur due to the deficient data collection process. This imbalance can…
Adaptive SVM+: Learning with Privileged Information for Domain Adaptation
Nikolaos Sarafianos, Michalis Vrigkas, Ioannis A. Kakadiaris
Incorporating additional knowledge in the learning process can be beneficial for several computer vision and machine learning tasks. Whether privileged information originates from…
Curriculum Learning for Multi-Task Classification of Visual Attributes
Nikolaos Sarafianos, Theodore Giannakopoulos, Christophoros Nikou +1
Visual attributes, from simple objects (e.g., backpacks, hats) to soft-biometrics (e.g., gender, height, clothing) have proven to be a powerful representational approach for many a…
End-to-end 3D face reconstruction with deep neural networks
Pengfei Dou, Shishir K. Shah, Ioannis A. Kakadiaris
Monocular 3D facial shape reconstruction from a single 2D facial image has been an active research area due to its wide applications. Inspired by the success of deep neural network…
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…