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A Deep Face Identification Network Enhanced by Facial Attributes Prediction [article]

Fariborz Taherkhani, Nasser M. Nasrabadi, Jeremy Dawson
2018 arXiv   pre-print
In this paper, we propose a new deep framework which predicts facial attributes and leverage it as a soft modality to improve face identification performance.  ...  Our model is an end to end framework which consists of a convolutional neural network (CNN) whose output is fanned out into two separate branches; the first branch predicts facial attributes while the  ...  Deep Joint Facial Attributes Prediction and Face Identification Model The proposed architecture predicts facial attributes and uses them as an auxiliary modality to recognize face images.  ... 
arXiv:1805.00324v1 fatcat:dd4c64zjczfflj6uhal5tf7qe4

A Deep Face Identification Network Enhanced by Facial Attributes Prediction

Fariborz Taherkhani, Nasser M. Nasrabadi, Jeremy Dawson
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
In this paper, we propose a new deep framework which predicts facial attributes and leverage it as a soft modality to improve face identification performance.  ...  Our model is an end to end framework which consists of a convolutional neural network (CNN) whose output is fanned out into two separate branches; the first branch predicts facial attributes while the  ...  Deep Joint Facial Attributes Prediction and Face Identification Model The proposed architecture predicts facial attributes and uses them as an auxiliary modality to recognize face images.  ... 
doi:10.1109/cvprw.2018.00097 dblp:conf/cvpr/TaherkhaniND18 fatcat:6u247e7ue5bzdporpv7lust3sy

Deep Sketch-Photo Face Recognition Assisted by Facial Attributes [article]

Seyed Mehdi Iranmanesh, Hadi Kazemi, Sobhan Soleymani, Ali Dabouei, Nasser M. Nasrabadi
2018 arXiv   pre-print
The proposed Attribute-Assisted Deep Con- volutional Neural Network (AADCNN) method exploits the facial attributes and leverages the loss functions from the facial attributes identification and face verification  ...  We propose a cou- pled deep neural network architecture which utilizes facial attributes in order to improve the sketch-photo recognition performance.  ...  Multi-Attribute Prediction and Identification Task: The objective of this model is to predict a set of attributes using a face photo or an sketch.  ... 
arXiv:1808.00059v1 fatcat:aacadvlctbfrpkttkj2lgvt6qi

Feature Level Fusion from Facial Attributes for Face Recognition [article]

Mohammad Rasool Izadi
2021 arXiv   pre-print
We introduce a deep convolutional neural networks (CNN) architecture to classify facial attributes and recognize face images simultaneously via a shared learning paradigm to improve the accuracy for facial  ...  Specifically, we use a shared CNN architecture that jointly predicts facial attributes and recognize face images simultaneously via a shared learning parameters, and then we use facial attribute features  ...  In this study, we use facial attributes as a soft modality to enhance face recognition.  ... 
arXiv:1909.13126v2 fatcat:avbyxyrrb5bcvdqnyzwupsbt7a

AnonymousNet: Natural Face De-Identification with Measurable Privacy [article]

Tao Li, Lei Lin
2019 arXiv   pre-print
The framework encompasses four stages: facial attribute estimation, privacy-metric-oriented face obfuscation, directed natural image synthesis, and adversarial perturbation.  ...  Not only do we achieve the state-of-the-arts in terms of image quality and attribute prediction accuracy, we are also the first to show that facial privacy is measurable, can be factorized, and accordingly  ...  Acknowledgment The authors especially thank Professor Chris Clifton for insightful discussions in differential privacy and privacy metrics in the context of facial images.  ... 
arXiv:1904.12620v1 fatcat:545gr4nvr5cw5hml5feubxzbcm

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
Intra Prediction of Variable Block Size Yu, Lu Compressing Facial Makeup Transfer Network by Collaborative Distillation and Kernel Decomposition Yu, Zengrui Attention-Guided Fusion Network of  ...  Hu, Xinyi Compressing Facial Makeup Transfer Network by Collaborative Distillation and Kernel Decomposition Hu, Yuzhang Sensitivity-Aware Bit Allocation for Intermediat Deep Feature Compression  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

Boosting Deep Face Recognition via Disentangling Appearance and Geometry [article]

Ali Dabouei, Fariborz Taherkhani, Sobhan Soleymani, Jeremy Dawson, Nasser M. Nasrabadi
2020 arXiv   pre-print
Furthermore, we show that the knowledge leaned by the proposed method can favor other face-related tasks, such as attribute prediction.  ...  We demonstrate that the proposed approach enhances the performance of deep face recognition models by assisting the training process in two ways.  ...  Transferring the knowledge learned by the face recognition models enhanced by DAG consistently improves the performance of attribute prediction.  ... 
arXiv:2001.04559v1 fatcat:opeumvphpzalxn2p2rwndjp55a

Integrated Multi-Model Face Shape and Eye Attributes Identification for Hair Style and Eyelashes Recommendation

Theiab Alzahrani, Waleed Al-Nuaimy, Baidaa Al-Bander
2021 Computation  
Gender identification system has been realised and designed by implementing a deep learning-based approach.  ...  To achieve the aim, we develop a multi-model system comprising three separate models; each model targeted a different task, including; face shape classification, eye attribute identification and gender  ...  The proposed framework integrates three main models: face shape classification model, gender prediction model for predicting the gender of user, and eye attribute identification model to make a decision  ... 
doi:10.3390/computation9050054 doaj:75a66d4462c2400f9645f637bf214fff fatcat:elrciceyc5b7fkgdwsua5pnuau

Design of a Face Recognition System based on Convolutional Neural Network (CNN)

Y. Said, M. Barr, H. E. Ahmed
2020 Zenodo  
Face recognition is an important function of video surveillance systems, enabling verification and identification of people who appear in a scene often captured by a distributed network of cameras.  ...  This paper aims to develop a face recognition application for a biometric system based on Convolutional Neural Networks.  ...  ACKNOWLEDGMENT The authors wish to acknowledge the support of this research by the grant N°ENG-2018-3-9-F-7880 from the Deanship of the Scientific Research in Northern Border University, Arar, Saudi Arabia  ... 
doi:10.5281/zenodo.3934499 fatcat:eh2w3ffj4vgfteemactzg3jyta

A Survey of Deep Facial Attribute Analysis [article]

Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li, Ran He
2019 arXiv   pre-print
In this paper, we provide a comprehensive survey of deep facial attribute analysis from the perspectives of both estimation and manipulation.  ...  First, we summarize a general pipeline that deep facial attribute analysis follows, which comprises two stages: data preprocessing and model construction.  ...  Apart from employing features learned by attribute prediction to assist face recognition, joint and incorporative learning of facial attribute relevant tasks can further enhance their respective robustness  ... 
arXiv:1812.10265v3 fatcat:tezgo2angvfefbttuoodnss6t4

Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks

Guosheng Hu, Yang Hua, Yang Yuan, Zhihong Zhang, Zheng Lu, Sankha S. Mukherjee, Timothy M. Hospedales, Neil M. Robertson, Yongxin Yang
2017 2017 IEEE International Conference on Computer Vision (ICCV)  
Conclusion We considered the problem of enhancing face recognition by incorporating predicted attributes.  ...  Facial attributes have been applied to enhance face verification, primarily in the case of cross-modal matching, by filtering [19, 54] (requiring potential FRF matches to have the correct gender, for  ... 
doi:10.1109/iccv.2017.404 dblp:conf/iccv/HuHYZLMHRY17 fatcat:6emro5oxurgqxajasqpqiw7oke

A Survey of Deep Facial Attribute Analysis

Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li, Ran He
2020 International Journal of Computer Vision  
In this paper, we provide a comprehensive survey of deep facial attribute analysis from the perspectives of both estimation and manipulation.  ...  First, we summarize a general pipeline that deep facial attribute analysis follows, which comprises two stages: data preprocessing and model construction.  ...  Apart from employing features learned by attribute prediction to assist face recognition, joint and incorporative learning of facial attribute relevant tasks can further enhance their respective robustness  ... 
doi:10.1007/s11263-020-01308-z fatcat:xmlukvd5qbenzkzjacefhcnope

Cloud-based architecture for face identification with deep learning using convolutional neural network

Aditya Herlambang, Putu Wira Buana, I Nyoman Piarsa
2021 Indonesian Journal of Electrical Engineering and Computer Science  
We proposed a cloud-based architecture for face identification with deep learning using convolutional neural network.  ...  Face identification in this study used a cloud-based engine with four stages, namely face detection with histogram of oriented gradients (HOG), image enhancement, feature extraction using convolutional  ...  In deep learning, facial feature can be extracted by single CNN architecture from large amount of image containing faces. CNN is intended to process data that has a known network such as a topology.  ... 
doi:10.11591/ijeecs.v23.i2.pp811-820 fatcat:occb4nlu4baa3bu4gchdw6jlo4

Enhancement of Patient Facial Recognition through Deep Learning Algorithm: ConvNet

Edeh Michael Onyema, Piyush Kumar Shukla, Surjeet Dalal, Mayuri Neeraj Mathur, Mohammed Zakariah, Basant Tiwari, Kalidoss Rajakani
2021 Journal of Healthcare Engineering  
In this study, we present a technique for facial expression recognition based on deep learning algorithm: convolutional neural network (ConvNet).  ...  The study concludes that deep l\earning-enabled facial expression recognition techniques enhance accuracy, better facial recognition, and interpretation of facial expressions and features that promote  ...  Convolutional neural networks [21] , a subfield of deep learning, are used to recognise faces (CNN). It is a multilayer network that uses categorization to do a certain task.  ... 
doi:10.1155/2021/5196000 pmid:34912534 pmcid:PMC8668299 fatcat:7bkm6zvvpncblpnlju72w6ro7a

FATAUVA-Net: An Integrated Deep Learning Framework for Facial Attribute Recognition, Action Unit Detection, and Valence-Arousal Estimation

Wei-Yi Chang, Shih-Huan Hsu, Jen-Hsien Chien
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
In this paper, we propose an integrated deep learning framework for facial attribute recognition, AU detection, and V-A estimation.  ...  Besides, the AU detector is trained based on the convolutional neural network (CNN) for facial attribute recognition.  ...  [22] proposed a cascaded deep learning framework for attribute prediction. Torfason et al.  ... 
doi:10.1109/cvprw.2017.246 dblp:conf/cvpr/ChangHC17 fatcat:dqxksqqer5az3dvdzsvgqdjdhm
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