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Sejong face database: A multi-modal disguise face database

Usman Cheema, Seungbin Moon
2021 Computer Vision and Image Understanding  
In this paper, we present a multimodal disguised face dataset to facilitate the disguised face recognition research.  ...  Disguised face recognition is one of the emerging issues for access control systems, such as security checkpoints at the borders.  ...  Disguised Face Recognition Face recognition is performed on the presented datasets using Squeeze and Excitation blocks [26] using ResNet backbone as presented in VGGFace2 [27] .  ... 
doi:10.1016/j.cviu.2021.103218 fatcat:gb5ctgltzbeo7inmvf66eknoqe

A CNN Model for Head Pose Recognition using Wholes and Regions

Ardhendu Behera, Andrew G Gidney, Zachary Wharton, Daniel Robinson, Keiron Quinn
2019 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)  
We also compare our pose recognition performance with the latest OpenFace 2.0 facial behavior analysis toolkit. In addition, we contribute head pose annotation to a large-scale dataset (VGGFace2).  ...  Extensive experimental results on head pose recognition using four different large-scale datasets, demonstrate that the proposed approach outperforms many state-of-the-art deep CNN models.  ...  The GPU used in this research is generously donated by the NVIDIA Corporation.  ... 
doi:10.1109/fg.2019.8756536 dblp:conf/fgr/BeheraGWRQ19 fatcat:wxvp27qczndc5ad2edjj5dd7jm

Diagonal Symmetric Pattern based Illumination Invariant Measure for Severe Illumination Variation Face Recognition

Changhui Hu, Fei Wu, Jian Yu, Xiaoyuan Jing, Xiaobo Lu, Pan Liu
2020 IEEE Access  
This paper proposes a novel diagonal symmetric pattern (DSP) to develop the illumination invariant measure for severe illumination variation face recognition.  ...  Finally, the experimental results on the Extended Yale B, CMU PIE, AR, and VGGFace2 face databases indicate that the proposed methods are efficient to tackle severe illumination variations.  ...  . 4) VGGFACE2 VGGFace2 images are composed of large scale bright internet face images with large pose/expression variations, and illumination variations of VGGFace2 are not as severe as those of Extended  ... 
doi:10.1109/access.2020.2983837 fatcat:pjk5docosrbmhd2yynuboucyxa

Improving Makeup Face Verification by Exploring Part-Based Representations [article]

Marcus de Assis Angeloni, Helio Pedrini
2021 arXiv   pre-print
Despite significant advances in face recognition technology with the adoption of convolutional neural networks, there are still open challenges, such as when there is makeup in the face.  ...  Recently, we have seen an increase in the global facial recognition market size.  ...  face representations using attention-based multi-branch learning network.  ... 
arXiv:2101.07338v2 fatcat:7esflh4gbfekvnuzhghkheiajq

Multi-Face: Self-supervised Multiview Adaptation for Robust Face Clustering in Videos [article]

Krishna Somandepalli, Rajat Hebbar, Shrikanth Narayanan
2020 arXiv   pre-print
However, local face tracking in videos can be used to mine samples belonging to same/different persons by examining the faces co-occurring in a video frame.  ...  In this work, we use this idea of self-supervision to harvest large amounts of weakly labeled face tracks in movies.  ...  VggFace2 [9] is a ResNet-50 neural network trained on the large-scale VggFace2 dataset for the task of face classification.  ... 
arXiv:2008.11289v1 fatcat:mjmo66psm5ggxbebaacx4f525y

Investigating the Impact of Inclusion in Face Recognition Training Data on Individual Face Identification [article]

Chris Dulhanty, Alexander Wong
2020 arXiv   pre-print
with their face being used to train dual-use technologies that can enable mass surveillance.  ...  In this work, we audit ArcFace, a state-of-the-art, open source face recognition system, in a large-scale face identification experiment with more than one million distractor images.  ...  Deep Face Recognition Rapid improvements in image classification in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) [38] by AlexNet [23] , ZFNet [54] , GoogLeNet [42] and ResNet [  ... 
arXiv:2001.03071v2 fatcat:sceemlshtfcohba6lokf4cv5me

Bagging ensemble for deep learning based gender recognition using test-time augmentation on large-scale datasets

2021 Turkish Journal of Electrical Engineering and Computer Sciences  
Augmentation techniques are often used 6 in the learning phase of the CNNs to improve the generalization ability.  ...  We present a bagging ensemble of convolutional networks in combination with the test-time augmentation 4 technique to improve performance on the cross-dataset gender recognition problem.  ...  12 that VGGFace2, CelebA, and IMDb datasets provide better average accuracy than other datasets.  ... 
doi:10.3906/elk-2008-166 fatcat:ozmqaaavgrgfhoq7gdj3sq7p4m

DAIL: Dataset-Aware and Invariant Learning for Face Recognition [article]

Gaoang Wang, Lin Chen, Tianqiang Liu, Mingwei He, Jiebo Luo
2021 arXiv   pre-print
To achieve good performance in face recognition, a large scale training dataset is usually required.  ...  A simple yet effective way to improve recognition performance is to use a dataset as large as possible by combining multiple datasets in the training.  ...  Two large scale reasonable since the MS1M dataset has 8 times more IDs and training datasets, MS1M and VGGFace2, are used for the is 10 times larger than the CASIA dataset.  ... 
arXiv:2101.05419v1 fatcat:l7n4rr3r5ravrdlg5byhjho57u

Git Loss for Deep Face Recognition [article]

Alessandro Calefati, Muhammad Kamran Janjua, Shah Nawaz, Ignazio Gallo
2018 arXiv   pre-print
Convolutional Neural Networks (CNNs) have been widely used in computer vision tasks, such as face recognition and verification, and have achieved state-of-the-art results due to their ability to capture  ...  achieves state-of-the-art accuracy on two major face recognition benchmark datasets: Labeled Faces in the Wild (LFW) and YouTube Faces (YTF).  ...  In this paper, we employ all three attributes associated with face recognition. We use a large scale publicly available dataset, VGGFace2, to train the powerful Inception ResNet-V1 network.  ... 
arXiv:1807.08512v4 fatcat:i63mpj6xijemfajbrul7ezl2ye

Efficient facial representations for age, gender and identity recognition in organizing photo albums using multi-output ConvNet

Andrey V. Savchenko
2019 PeerJ Computer Science  
In the second stage of the proposed approach, extracted faces are grouped using hierarchical agglomerative clustering techniques.  ...  Here the MobileNet is modified and is preliminarily trained to perform face recognition in order to additionally recognize age and gender.  ...  large-scale face recognition datasets.  ... 
doi:10.7717/peerj-cs.197 pmid:33816850 pmcid:PMC7924510 fatcat:5dbeokptifchtfiebjm6zpzhsy

CNN-based Gender Prediction in Uncontrolled Environments

Kazım YILDIZ, Engin GÜNEŞ, Anil BAS
2021 Düzce Üniversitesi Bilim ve Teknoloji Dergisi  
By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification and face analysis in the fields of image processing and computer vision.  ...  Yapılan deneyler sonucunda VGGFace2 veri seti üzerinde 93.71% ve Adience veri seti üzerinde 85.52% oranında başarı sağlanmıştır.  ...  The experimental results show that the suggested method works well on multi-scale face detection problems [23] .  ... 
doi:10.29130/dubited.763427 fatcat:z2fpt3ay4zbuplnyiqquzk72mm

Universal Adversarial Spoofing Attacks against Face Recognition [article]

Takuma Amada, Seng Pei Liew, Kazuya Kakizaki, Toshinori Araki
2021 arXiv   pre-print
We assess the vulnerabilities of deep face recognition systems for images that falsify/spoof multiple identities simultaneously.  ...  Our results indicate that a multiple-identity attack is a real threat and should be taken into account when deploying face recognition systems.  ...  [17] considers Master Faces, multi-identity spoofing images crafted using GANs.  ... 
arXiv:2110.00708v1 fatcat:6fou4zag4jdc7pnaaydwhdpcxm

A Method for Curation of Web-Scraped Face Image Datasets [article]

Kai Zhang, Vítor Albiero, Kevin W. Bowyer
2020 arXiv   pre-print
We conduct the curation on the Asian Face Dataset (AFD) and VGGFace2 test dataset.  ...  Web-scraped, in-the-wild datasets have become the norm in face recognition research.  ...  To the best of our knowledge, there is not a widely-used, publicly-available dataset with a large number of Asian faces built for face recognition testing.  ... 
arXiv:2004.03074v1 fatcat:lvvdnk6lc5b2xn7jweby3fcwmq

Measuring Hidden Bias within Face Recognition via Racial Phenotypes [article]

Seyma Yucer, Furkan Tektas, Noura Al Moubayed, Toby P. Breckon
2021 arXiv   pre-print
Furthermore, we contribute corresponding phenotype attribute category labels for two face recognition tasks: RFW for face verification and VGGFace2 (test set) for face identification.  ...  Recent work reports disparate performance for intersectional racial groups across face recognition tasks: face verification and identification.  ...  Use of VGGFace2 and RFW: We conduct our experiments on two different face datasets which are publicly available for research use only.  ... 
arXiv:2110.09839v1 fatcat:5lz62g5i7ncy7bdgff33gpndhi

Profile to Frontal Face Recognition in the Wild Using Coupled Conditional GAN [article]

Fariborz Taherkhani, Veeru Talreja, Jeremy Dawson, Matthew C. Valenti, Nasser M. Nasrabadi
2021 arXiv   pre-print
The efficacy of our approach compared with the state-of-the-art is demonstrated using the CFP, CMU Multi-PIE, IJB-A, and IJB-C datasets.  ...  The major reason for poor performance in handling of profile faces is that it is inherently difficult to learn pose-invariant deep representations that are useful for profile face recognition.  ...  VGGFace2 is a large-scale face recognition dataset, where the images are downloaded from Google Image Search and have large variations in pose, age, illumination, and ethnicity.  ... 
arXiv:2107.13742v1 fatcat:jmjnrsla3vesvoc7z44smprtgi
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