Chi Nhan Duong

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The " interpretation through synthesis " , i.e. Active Appearance Models (AAMs) method [1], has become one of the most successful and popular face modeling approaches over the last two decades. Given a new face image , the purpose is to " describe " that image by generating a new synthesized image that is similar to it as much as possible. This aim can be(More)
Modeling the face aging process is a challenging task due to large and non-linear variations present in different stages of face development. This paper presents a deep model approach for face age progression that can efficiently capture the non-linear aging process and automatically synthesize a series of age-progressed faces in various age ranges. In this(More)
—The " interpretation through synthesis " approach to analyze face images, particularly Active Appearance Models (AAMs) method, has become one of the most successful face modeling approaches over the last two decades. AAM models have ability to represent face images through synthesis using a controllable parameterized Principal Component Analysis (PCA)(More)
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