A Novel ANN based Approach for Angle Invariant Face Verification

2007 ◽  
Author(s):  
Basabi Chakraborty
Keyword(s):  
Face Verification

CROSS-AGE FACE VERIFICATION USING FACE AGING

2020 ◽  
Author(s):  
Alankrit Khanna ◽  
Anisha Thakur ◽  
Aprajita Tewari ◽  
Aruna Bhat
Keyword(s):  
Face Verification ◽  
Face Aging

DDAT: Dual Domain Adaptive Translation for Low-Resolution Face Verification in the Wild

2021 ◽  
pp. 108107
Author(s):  
Qianfen Jiao ◽  
Rui Li ◽  
Wenming Cao ◽  
Jian Zhong ◽  
Si Wu ◽  
...  
Keyword(s):  
Face Verification ◽  
Low Resolution ◽  
In The Wild ◽  
Dual Domain

scholarly journals Multi-Task Learning Using Task Dependencies for Face Attributes Prediction

2019 ◽  
Vol 9 (12) ◽  
pp. 2535
Author(s):  
Di Fan ◽  
Hyunwoo Kim ◽  
Jummo Kim ◽  
Yunhui Liu ◽  
Qiang Huang
Keyword(s):  
Human Computer Interaction ◽  
Video Surveillance ◽  
State Of The Art ◽  
Learning Task ◽  
Face Verification ◽  
Task Learning ◽  
The World ◽  
In The Wild ◽  
And Gender ◽  
Learning Architectures

Face attributes prediction has an increasing amount of applications in human–computer interaction, face verification and video surveillance. Various studies show that dependencies exist in face attributes. Multi-task learning architecture can build a synergy among the correlated tasks by parameter sharing in the shared layers. However, the dependencies between the tasks have been ignored in the task-specific layers of most multi-task learning architectures. Thus, how to further boost the performance of individual tasks by using task dependencies among face attributes is quite challenging. In this paper, we propose a multi-task learning using task dependencies architecture for face attributes prediction and evaluate the performance with the tasks of smile and gender prediction. The designed attention modules in task-specific layers of our proposed architecture are used for learning task-dependent disentangled representations. The experimental results demonstrate the effectiveness of our proposed network by comparing with the traditional multi-task learning architecture and the state-of-the-art methods on Faces of the world (FotW) and Labeled faces in the wild-a (LFWA) datasets.

scholarly journals Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks

2017 ◽  
Vol 126 (2-4) ◽  
pp. 272-291 ◽  
Author(s):  
Jun-Cheng Chen ◽  
Rajeev Ranjan ◽  
Swami Sankaranarayanan ◽  
Amit Kumar ◽  
Ching-Hui Chen ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Face Verification ◽  
Deep Convolutional Neural Networks

Advanced Joint Bayesian Method for Face Verification

2015 ◽  
Vol 10 (2) ◽  
pp. 346-354 ◽  
Author(s):  
Yicong Liang ◽  
Xiaoqing Ding ◽  
Jing-Hao Xue
Keyword(s):  
Bayesian Method ◽  
Face Verification
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