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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.  ...  In this paper, we conduct an in-depth survey of facial attribute analysis based on deep learning, including FAE and FAM.  ... 
arXiv:1812.10265v3 fatcat:tezgo2angvfefbttuoodnss6t4

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.  ...  In this paper, we conduct an in-depth survey of facial attribute analysis based on deep learning, including FAE and FAM.  ... 
doi:10.1007/s11263-020-01308-z fatcat:xmlukvd5qbenzkzjacefhcnope

Understanding Beauty via Deep Facial Features [article]

Xudong Liu, Tao Li, Hao Peng, Iris Chuoying Ouyang, Taehwan Kim, Ruizhe Wang
2019 arXiv   pre-print
We first deploy a deep convolutional neural network (CNN) to extract facial attributes, and then investigate correlations between these features and attractiveness on two large-scale datasets labelled  ...  In this paper, we present a novel study on mining beauty semantics of facial attributes based on big data, with an attempt to objectively construct descriptions of beauty in a quantitative manner.  ...  We propose a method and a novel perspective of beauty understanding via deep facial features, which allows us to analyze which facial attributes contribute positively or negatively to beauty perception  ... 
arXiv:1902.05380v2 fatcat:hzgfwuowqnaw5e2ixtioukuniy

AN OVERVIEW OF FACIAL ATTRIBUTE LEARNING

Phùng Thái Thiên Trang, Fukuzawa Masayuki, Lý Quốc Ngọc
2021 Tạp chí Khoa học  
A typical CNN model for attribute learning Zhang et al. (2014) proposed PANDA (Pose Align Networks for Deep Attribution), a Deep CNN to classify attributes based on parts of the face image.  ...  Using bounding boxes for face detection, authors used VGG-16 for analysis of facial attributes (eyeglasses, smiles, kisses) on the CelebA and LFWA datasets to achieve an average error comparable to the  ... 
doi:10.54607/hcmue.js.18.3.2896(2021) fatcat:trplwbymprcwbencm7err3s7vm

Perception of Autism Spectrum Disorder Children by Envisaging Emotions from the Facial Images

2020 International Journal of Engineering and Advanced Technology  
In this paper a new methodology is proposed using optimized deep learning methods to predict ASD in children of age 1 to 10 years.  ...  Facial expression can also be used in various fields like emotion recognition, market analysis, prediction neurological disorder percentage, psychological problems and so on.  ...  CONCLUSION AND FUTURE WORK Present paper proposed a Deep Neural Network model with multi label classification to predict ASD/NoASD based on facial emotion in ASD and NoASD children.  ... 
doi:10.35940/ijeat.b1960.1210220 fatcat:3k5xypl3yrbotc7ycb6kk3ekji

Understanding Beauty via Deep Facial Features

Xudong Liu, Tao Li, Hao Peng, Iris Chuoying Ouyang, Taehwan Kim, Ruizhe Wang
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
We propose a method and a novel perspective of beauty understanding via deep facial features, which allows us to analyze which facial attributes contribute positively or negatively to beauty perception  ...  The sample modified facial attributes from left to right are small nose to big nose, male to female, no-makeup to makeup, and young to aged.  ...  We further manipulate several facial attributes with a GAN based approach, and validate our findings with a large-scale user survey.  ... 
doi:10.1109/cvprw.2019.00034 dblp:conf/cvpr/LiuLPOKW19 fatcat:ivziqfodhbaf7ozsr25c7jbmre

Efficient Visual Recognition

Li Liu, Matti Pietikäinen, Jie Qin, Wanli Ouyang, Luc Van Gool
2020 International Journal of Computer Vision  
Table 1 1 A brief summary of accepted papers "Efficiency" category Paper title Studied visual recognition problem Survey A survey to deep facial attribute analysis Facial attribute analysis Network  ...  Learning hashing codes; Surveys The paper "A Survey of Deep Facial Attribute Analysis", by Xin Zheng, Yanqing Guo, Huaibo Huang, Yi Li and Ran He, gives a comprehensive survey of deep facial attribute  ... 
doi:10.1007/s11263-020-01351-w fatcat:mbcq6shmerbo5njayscgb3t4rq

Deep Learning-based Face Super-resolution: A Survey

Junjun Jiang, Chenyang Wang, Xianming Liu, Jiayi Ma
2023 ACM Computing Surveys  
To date, few summaries of the studies on the deep learning-based FSR are available. In this survey, we present a comprehensive review of deep learning-based FSR methods in a systematic manner.  ...  Second, we elaborate on the facial characteristics and popular datasets used in FSR. Third, we roughly categorize existing methods according to the utilization of facial characteristics.  ...  Therefore, to recover facial images with a much clearer facial structure, researchers begin to develop priorguided FSR methods. Deep Learning-based Face Super-resolution: A Survey 13:13 Fig. 5 .  ... 
doi:10.1145/3485132 fatcat:gxaod3eqs5gkbmtow3k4jrrpvy

Role of Group Level Affect to Find the Most Influential Person in Images [chapter]

Shreya Ghosh, Abhinav Dhall
2019 Landolt-Börnstein - Group III Condensed Matter  
In order to identify "Most Influential Person", we proposed a DNN based Multiple Instance Learning (Deep MIL) method which takes deep facial features as input.  ...  In order to identify the main visual cues for "Most Influential Person", we conducted a user survey.  ...  We use group affect for choosing the same number of faces across images for further analysis because in the survey result people mention emotion attributes for choosing a particular face (for example '  ... 
doi:10.1007/978-3-030-11012-3_39 fatcat:hvn3khpyyzaxzcqzqjd2l6qa6u

Deep Personality Trait Recognition: A Survey

Xiaoming Zhao, Zhiwei Tang, Shiqing Zhang
2022 Frontiers in Psychology  
Motivated by the great success of deep learning methods in various tasks, a variety of deep neural networks have increasingly been employed to learn high-level feature representations for automatic personality  ...  This paper systematically presents a comprehensive survey on existing personality trait recognition methods from a computational perspective.  ...  In this work, our contributions can be summarized as follows: (1) We provide an up-to-date literature survey on deep personality trait analysis from a perspective of both single modality and multiple modalities  ... 
doi:10.3389/fpsyg.2022.839619 pmid:35645923 pmcid:PMC9136483 fatcat:5eh2ohzjwff5jb4yjn6rzrw5ye

Cloud-Based Facial Expression Recognition System for Customer Satisfaction in Distribution Sectors

Jiyoon Lee, Wonil Hwang
2020 Innovative Computing Information and Control Express Letters, Part B: Applications  
The survey method can, however, be expensive, in terms of man power and time, and it is difficult to grasp customer complaints in real time.  ...  In this matter, it is essential how to measure the customer satisfaction, but the traditional methods, like the survey method, are still widely used in the distribution process.  ...  In this paper, we propose a system architecture that can automate the existing passive satisfaction survey method by using image analysis method based on deep learning.  ... 
doi:10.24507/icicelb.11.02.173 fatcat:lj6aibkfc5dnjh2ios3tb23xyu

Deep Learning-based Face Super-Resolution: A Survey [article]

Junjun Jiang, Chenyang Wang, Xianming Liu, Jiayi Ma
2021 arXiv   pre-print
To date, few summaries of the studies on the deep learning-based FSR are available. In this survey, we present a comprehensive review of deep learning-based FSR methods in a systematic manner.  ...  Second, we elaborate on the facial characteristics and popular datasets used in FSR. Third, we roughly categorize existing methods according to the utilization of facial characteristics.  ...  We also compare the performance of state-of-the-arts and give some deep analysis.  ... 
arXiv:2101.03749v2 fatcat:q56d2mpn4rfyzmi5fo36d2ecja

Anatomizing Bias in Facial Analysis

Richa Singh, Puspita Majumdar, Surbhi Mittal, Mayank Vatsa
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Existing facial analysis systems have been shown to yield biased results against certain demographic subgroups.  ...  We also discuss open challenges in the field of biased facial analysis.  ...  This research presents a systematic survey of bias in facial analysis tasks as opposed to the broader topic of biometrics addressed in (Drozdowski et al. 2020) .  ... 
doi:10.1609/aaai.v36i11.21500 fatcat:lbuwkwaganfkxlzy55ir5lyngi

Deep CNN and Deep GAN in Computational Visual Perception-Driven Image Analysis

R. Nandhini Abirami, P. M. Durai Raj Vincent, Kathiravan Srinivasan, Usman Tariq, Chuan-Yu Chang, Dr Shahzad Sarfraz
2021 Complexity  
In-depth analysis of deep generative adversarial network applications, namely, image-to-image translation, image denoising, face aging, and facial attribute editing, is done.  ...  The survey explores various deep learning techniques adapted to solve computer vision problems using deep convolutional neural networks and deep generative adversarial networks.  ...  Face Aging and Facial Attribute Editing. Deep GANbased methods have been proposed to alter facial attributes to anticipate a person's future look.  ... 
doi:10.1155/2021/5541134 fatcat:xluxbl7kojbvxpjq5u726d3djm

2021 Index IEEE Transactions on Affective Computing Vol. 12

2022 IEEE Transactions on Affective Computing  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  2021 707-721 Bio-Inspired Deep Attribute Learning Towards Facial Aesthetic Prediction. viduals and Groups.  ...  ., +, TAFFC April -June 2021 377-390 Bio-Inspired Deep Attribute Learning Towards Facial Aesthetic Prediction. Xu, M., +, TAFFC Jan.  ... 
doi:10.1109/taffc.2021.3132546 fatcat:qjxf4chxybaelmyrlnhiesanai
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