Master's Thesis Synthetic Faces for Age Estimation Artifacts, Domain Shift, Label Quality
Fraunhofer-Gesellschaft
ThesisGerman needed: none
Still open on 1 NovWhat you'll do
- Goal of the Master’s Thesis
- The goal of this master’s thesis is to systematically investigate why synthetic face images have so far been of only limited use for training age estimation models. In particular, artifacts of different generative models are to be identified, their influence on age estimation models analyzed, and methods for reducing the domain shift developed. In addition, the thesis will examine how reliable the specified age labels of synthetically generated persons actually are.
- Results
- The expected outcome is a systematic characterization of the differences between real and synthetic face images from various generative models. The thesis should show which artifacts or statistical properties make it possible to distinguish synthetic from real images, and to what extent these features are relevant for age estimation models.
- Furthermore, methods for reducing the domain shift are to be developed or investigated, and their effects on training with mixed real and synthetic datasets evaluated. In particular, the thesis should clarify whether lower distinguishability between real and synthetic images also goes along with improved generalization of age estimation models.
- Another focus is on the reliability of synthetic age labels. The thesis is expected to provide sound findings on how accurately different generative methods reproduce the desired ages, in which age ranges systematic errors occur, how these can be detected, and what influence this label noise has on training.
- Based on this, the thesis should derive guidelines on when and under which conditions synthetic face images can add value for age estimation, and which requirements must be met. The developed methods will be evaluated on publicly available benchmark datasets such as UTKFace, APPA-REAL, AgeDB or IMDB-WIKI, as well as on suitable synthetically generated datasets such as HDA-SynChildFaces.
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