2014
DOI: 10.1109/tifs.2014.2359646
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Age and Gender Estimation of Unfiltered Faces

Abstract: This paper concerns the estimation of facial attributes-namely, age and gender-from images of faces acquired in challenging, in the wild conditions. This problem has received far less attention than the related problem of face recognition, and in particular, has not enjoyed the same dramatic improvement in capabilities demonstrated by contemporary face recognition systems. Here, we address this problem by making the following contributions. First, in answer to one of the key problems of age estimation research… Show more

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Cited by 721 publications
(573 citation statements)
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References 63 publications
(77 reference statements)
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“…All the hidden units are ReLU, and the dropout technique has been also applied to the last hidden layer. Eidinger et al (2014) 88.60 LBP+CH+SIFT SVM Fazl-Ersi et al (2014) 91.59…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…All the hidden units are ReLU, and the dropout technique has been also applied to the last hidden layer. Eidinger et al (2014) 88.60 LBP+CH+SIFT SVM Fazl-Ersi et al (2014) 91.59…”
Section: Resultsmentioning
confidence: 99%
“…For instance, the AdaBoost and the SVM algorithms have been widely used in the literature (Baluja and Rowley (2007); Shan (2012); Eidinger et al (2014)). In this spirit, an excellent comparison of gender recognition techniques using different methods can be found in Dago-Casas et al (2011).…”
Section: Related Workmentioning
confidence: 99%
“…There are 26,580 face images from 2284 persons in the Adience dataset [41]. The images are with age and gender labels, which are collected from the Flickr albums and released by their authors under the Creative Commons (CC) license.…”
Section: Adience Datasetmentioning
confidence: 99%
“…Some sample images from LFW dataset are given in Figure 3. We have also used a relatively newly resealed adience dataset [6] to evaluate the result of our proposed method. The original dataset contains 26,580 face images of 2,284 different person.…”
Section: Datasetmentioning
confidence: 99%