EG 2019 - Short Papers
Permanent URI for this collection
Browse
Browsing EG 2019 - Short Papers by Author "Han, Tianqi"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
Item Towards Diverse Anime Face Generation: Active Label Completion and Style Feature Network(The Eurographics Association, 2019) Li, Hongyu; Han, Tianqi; Cignoni, Paolo and Miguel, EderIt is interesting to use an anime face as personal virtual image to replace the traditional sequence code. To generate diverse anime faces, this paper proposes a style-gender based anime GAN (SGA-GAN), where the gender is directly conditioned to ensure the gender differentiation, and style features serve as a condition to guarantee the style diversity. To extract style features, we train a style feature network (SFN) as a multi-task classifier to simultaneously fulfill gender classification, style classification, and image quality estimation. To make full use of available data, partly labeled or unlabeled, during the SFN training, we propose a label completion method to actively complete the missing gender or style labels. The active label completion is essentially a weakly-supervised learning process through ensembling three distinct classifiers to improve the generalization capability. Experiments verify that the active label completion can improve the model accuracy and the style feature as a condition can make better the diversity of generated anime faces.