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README.md
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https://paperswithcode.com/paper/new-benchmarks-for-asian-facial-recognition
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"This paper introduces a new Large-Scale Korean Influencer Dataset named KoIn. Our presented dataset contains many real-world photos of Korean celebrities in various environments that might contain stage lighting, backup dancers, and background objects. These various images can be useful for training classification models classifying K-influencers.
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https://paperswithcode.com/paper/new-benchmarks-for-asian-facial-recognition
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"Age, Gender, and Fine-Grained Ethnicity Prediction Using Convolutional Neural Networks for the East Asian Face Dataset"
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"Figure 5 presents the process of eye detection and segmentation and eye detection. The proposed dataset for eye detection includes eye images from face images of the WIDER FACE dataset [42] and the Wild East Asian Face Dataset (WEAFD) [43]. WEAFD images were collected and labeled into seven ethnic categories to explore the ethnic classification of East Asians. ...""
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license: apache-2.0
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https://paperswithcode.com/paper/new-benchmarks-for-asian-facial-recognition
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"This paper introduces a new Large-Scale Korean Influencer Dataset named KoIn. Our presented dataset contains many real-world photos of Korean celebrities in various environments that might contain stage lighting, backup dancers, and background objects. These various images can be useful for training classification models classifying K-influencers.
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https://paperswithcode.com/paper/new-benchmarks-for-asian-facial-recognition
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"Age, Gender, and Fine-Grained Ethnicity Prediction Using Convolutional Neural Networks for the East Asian Face Dataset" May 2017
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"Figure 5 presents the process of eye detection and segmentation and eye detection. The proposed dataset for eye detection includes eye images from face images of the WIDER FACE dataset [42] and the Wild East Asian Face Dataset (WEAFD) [43]. WEAFD images were collected and labeled into seven ethnic categories to explore the ethnic classification of East Asians. ...""
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"The ethnicity in this paper is considered as a three class classification problem (Asian, Black and White) and the approach is tested on ten different datasets and average classification accuracy over all datasets is 98.28%, 99.66% and 99.05% for Asian, African-American and Caucasian, respectively. The next research analysed was [17]. The authors explored the fine-grained ethnicity classification on East Asian population. ...""
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license: apache-2.0
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