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Unified Face Analysis by Iterative Multi-output Random Forests

Xiaowei Zhao, Tae-Kyun Kim, Wenhan Luo
2014 2014 IEEE Conference on Computer Vision and Pattern Recognition  
In this paper, we present a unified method for joint face image analysis, i.e., simultaneously estimating head pose, facial expression and landmark positions in real-world face images.  ...  Specifically, a hierarchical face analysis forest is learned to perform classification of pose and expression at the top level, while performing landmark positions regression at the bottom level.  ...  Acknowledgments This work is supported by EPSRC grant (EP/J012106/1) 3D intrinsic shape recognition.  ... 
doi:10.1109/cvpr.2014.228 dblp:conf/cvpr/ZhaoKL14 fatcat:ictgpdzzf5dkjbqxl6vt57syby

Facial Action Unit Detection with Multilayer Fused Multi-Task and Multi-Label Deep Learning Network

2019 KSII Transactions on Internet and Information Systems  
In this paper we propose a method for multi-view facial AU detection using a fused multilayer, multi-task, and multi-label deep learning network.  ...  The facial view recognition accuracy is 0.991. This shows that our multi-task, multi-label model could achieve good performance on the two tasks.  ...  Multi-task learning has been used many fields such as facial landmark detection, pose estimation, action recognition, face detection and so on. Zhang Z et al.  ... 
doi:10.3837/tiis.2019.11.015 fatcat:qrbozs5qhzhf3kxj3amtci6vfq

A Novel Multi-Feature Joint Learning Ensemble Framework for Multi-Label Facial Expression Recognition

Wanzhao Li, Mingyuan Luo, Peng Zhang, Wei Huang
2021 IEEE Access  
INDEX TERMS Multi-label, facial expression recognition, ResNet-18, deep learning.  ...  Some researchers have realized that facial expression recognition can be treated as a multi-label task, but they are still troubled by the inaccurate recognition of multi-label expressions.  ...  And sufficient experimental results confirm the proposed framework can provide more ability to learn discriminative features in a wide range of multi-label facial expression recognition tasks.  ... 
doi:10.1109/access.2021.3108838 fatcat:3zte75g56rf3zhhps4ffdlytp4

A Review of Facial Landmark Extraction in 2D Images and Videos Using Deep Learning

Matteo Bodini
2019 Big Data and Cognitive Computing  
The task of facial landmark extraction is fundamental in several applications which involve facial analysis, such as facial expression analysis, identity and face recognition, facial animation, and 3D  ...  Taking into account the most recent advances resulting from deep-learning techniques, the performance of methods for facial landmark extraction have been substantially improved, even on in-the-wild datasets  ...  The approach of TCDCN (Tasks Constrained Deep Convolutional Network) [33] consists of multi-task learning for optimizing the performance of five-point landmark extraction.  ... 
doi:10.3390/bdcc3010014 fatcat:cmqwb37tzbbhfdm23u53nvdpsu

Multi-task, multi-label and multi-domain learning with residual convolutional networks for emotion recognition [article]

Gerard Pons, David Masip
2018 arXiv   pre-print
We validate the proposal using two datasets acquired in non controlled environments, and an application to predict compound facial emotion expressions.  ...  In this paper, we propose to apply a multi-task learning loss function to share a common feature representation with other related tasks.  ...  Acknowledgements This research was supported by TIN2015-66951-C2-2-R grant from the Spanish Ministry of Economy and Competitiveness and NVIDIA Hardware grant program.  ... 
arXiv:1802.06664v1 fatcat:hjahssztdjfhtpyohb3i7342ja

Masked Face Analysis via Multi-Task Deep Learning

Vatsa S. Patel, Zhongliang Nie, Trung-Nghia Le, Tam V. Nguyen
2021 Journal of Imaging  
In particular, the multi-task deep learning model takes the data as inputs and shares their weight to yield predictions of age, expression, and gender for the masked face.  ...  Then, we propose a multi-task deep learning model to tackle the problem.  ...  Acknowledgments: We also gratefully acknowledge the support of NVIDIA Corporation with the donation of GPU used for this research. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jimaging7100204 pmid:34677290 pmcid:PMC8539947 fatcat:qd663hk45zdxnowvbe7unedj6m

Deep Adaptive Attention for Joint Facial Action Unit Detection and Face Alignment [article]

Zhiwen Shao, Zhilei Liu, Jianfei Cai, Lizhuang Ma
2018 arXiv   pre-print
Facial action unit (AU) detection and face alignment are two highly correlated tasks since facial landmarks can provide precise AU locations to facilitate the extraction of meaningful local features for  ...  In particular, multi-scale shared features are learned firstly, and high-level features of face alignment are fed into AU detection.  ...  Face Alignment with Multi-Task Learning: The correlation of facial expression recognition and face alignment has been leveraged in several face alignment works. For example, recently, Wu et al.  ... 
arXiv:1803.05588v1 fatcat:47zfmlsnorbgtd2vtlernln2ru

Novel multi-scale deep residual attention network for facial expression recognition

Dong Liu, Lifeng Wang, Zhiyong Wang, Longxi Chen
2020 The Journal of Engineering  
Recently, the deep convolutional neural networks (CNNs) have shown great success and for facial expression recognition (FER).  ...  for recognition.  ...  Multi-scale residual attention unit In this work, a multi-scale deep residual attention unit is proposed to perform he feature learning and exaction.  ... 
doi:10.1049/joe.2020.0183 fatcat:ak5pvhhpaja4ldnamdteywzds4

Joint Super-Resolution and Alignment of Tiny Faces

Yu Yin, Joseph Robinson, Yulun Zhang, Yun Fu
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Super-resolution (SR) and landmark localization of tiny faces are highly correlated tasks. On the one hand, landmark localization could obtain higher accuracy with faces of high-resolution (HR).  ...  Thus, we propose a joint alignment and SR network to simultaneously detect facial landmarks and super-resolve tiny faces.  ...  To address this problem, we present a novel synergistic multi-task framework that learns facial landmark localization and SR jointly.  ... 
doi:10.1609/aaai.v34i07.6962 fatcat:evjs3oabjrh5jpr26patt5essa

Joint Super-Resolution and Alignment of Tiny Faces [article]

Yu Yin, Joseph P. Robinson, Yulun Zhang, Yun Fu
2019 arXiv   pre-print
Super-resolution (SR) and landmark localization of tiny faces are highly correlated tasks. On the one hand, landmark localization could obtain higher accuracy with faces of high-resolution (HR).  ...  Thus, we propose a joint alignment and SR network to simultaneously detect facial landmarks and super-resolve tiny faces.  ...  To address this problem, we present a novel synergistic multi-task framework that learns facial landmark localization and SR jointly.  ... 
arXiv:1911.08566v1 fatcat:dmiae7vzs5dn7e2klpcc47xafu

Deep Learning for Micro-expression Recognition: A Survey [article]

Yante Li, Jinsheng Wei, Yang Liu, Janne Kauttonen, Guoying Zhao
2021 arXiv   pre-print
In this survey, we provide a comprehensive review of deep micro-expression recognition (MER), including datasets, deep MER pipeline, and the bench-marking of most influential methods.  ...  Different from macro-expressions, MEs are spontaneous, subtle, and rapid facial movements, leading to difficult data collection, thus have small-scale datasets.  ...  multi-task learning and transfer learning.  ... 
arXiv:2107.02823v4 fatcat:w2bqbvxw4zbc7jjnqmx2gmh5aa

The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances [article]

Hang Du, Hailin Shi, Dan Zeng, Xiao-Ping Zhang, Tao Mei
2021 arXiv   pre-print
With the recent development of deep learning techniques and large-scale datasets, deep face recognition has made remarkable progress and been widely used in many real-world applications.  ...  Given a natural image or video frame as input, an end-to-end deep face recognition system outputs the face feature for recognition.  ...  Besides, the multi-task learning is also a common routine to facilitate landmark localization with the related facial tasks, such as face detection [40, 174, 276, 312, 352] and facial attribute recognition  ... 
arXiv:2009.13290v4 fatcat:vlconzbbyzee5g3s7xnbjgv3ey

Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks

Behzad Hasani, Mohammad H. Mahoor
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Deep Neural Networks (DNNs) have shown to outperform traditional methods in various visual recognition tasks including Facial Expression Recognition (FER) .  ...  Our proposed method is evaluated using four publicly available databases in subject-independent and cross-database tasks and outperforms state-of-the-art methods.  ...  [38, 39] have used the Inception layer for the task of facial expression recognition and achieved state-of-the-art results.  ... 
doi:10.1109/cvprw.2017.282 dblp:conf/cvpr/HassaniM17a fatcat:4ags7s4pezbcnhrzvlndzzbh3y

Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks [article]

Behzad Hasani, Mohammad H. Mahoor
2017 arXiv   pre-print
Deep Neural Networks (DNNs) have shown to outperform traditional methods in various visual recognition tasks including Facial Expression Recognition (FER).  ...  Our proposed method is evaluated using four publicly available databases in subject-independent and cross-database tasks and outperforms state-of-the-art methods.  ...  [38, 39] have used the Inception layer for the task of facial expression recognition and achieved state-of-the-art results.  ... 
arXiv:1705.07871v1 fatcat:tpos3bx4t5aixnpd4wwogrktoq

Spontaneous Emotion Recognition from Facial Thermal Images [article]

Chirag Kyal
2020 arXiv   pre-print
The most often addressed tasks include face detection, facial landmark localization, face recognition and facial expression analysis.  ...  We have used USTC-NVIE database for training of a number of machine learning algorithms for facial landmark localization.  ...  Tang, "Facial landmark detection by deep multi-task learning," in European Conference on Computer Vision. Springer, 2014, pp. 94-108. -X. Zhu and D.  ... 
arXiv:2012.06973v1 fatcat:y6oikwo4qjflhabun4nfpfguou
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