# EC-GAN: Emotion-Controllable GAN for Face Image Completion
## 5 Conclusions  
This paper presents an Emotion-Controllable GAN model for customized realistic face completion. With the contribution of the emotion inference module and emotion control module, EC-GAN enables the emotion semantics to be disentangled from the native latent space and be modified independently, resulting in diverse expressions without affecting other facial features. In addition, the proposed EC-GAN correctly infers emotions and provides natural and plausible content for facial images where key regions are covered. Comprehensive experiments conducted on two publicly available face datasets establish that EC-GAN is capable of inferring emotions and controlling them more effectively than other state-of-the-art models. However, our model does not involve the control of the intensity of the generated expressions. We will conduct further research focusing on this problem and expect our EC-GAN to inspire new insights. Among future directions, one particularly interesting direction is to extend our model to the control of other attributions, such as hair color, makeup style, etc.  
Conceptualization, W.Y. and Y.C.; methodology, Y.C.; software, Y.C.; validation, Y.C. and W.Y.; resources, X.F. and H.H.; formal analysis, Y.C. and W.Y. data curation, Y.C.; writing--original draft preparation, Y.C.; writing--review and editing, W.Y., X.F. and H.H.; visualization, Y.C.; project administration, X.F.; supervision, W.Y. and X.F. All authors have read and agreed to the published version of the manuscript.  
This research was partially supported by the National Key R&D Projects under Grant 2020 YFA0714200 and the National Natural Science Foundation of China under Grant 11901443.  
Not applicable.  
The authors would like to thank the editor and anonymous reviewers for their valuable reviews.  
CFEED dataset is available at [[http://cbcs.leee.ohio-state.edu/compound.html](http://cbcs.leee.ohio-state.edu/compound.html)]([http://cbcs.leee.ohio-state.edu/compound.html](http://cbcs.leee.ohio-state.edu/compound.html)). CelebA-HQ dataset is available at [[http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)]([http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)).  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Appearance Loss** & **Perceptual Loss** & **FID \(\downarrow\)** & **IS \(\uparrow\)** & **SSIM \(\uparrow\)** \\ \hline  & & 22.17 & 25.66 & 0.81 \\ ✓ & & 21.92 & 26.93 & 0.84 \\  & ✓ & 21.43 & 27.08 & 0.87 \\ ✓ & ✓ & **20.61** & **28.14** & **0.89** \\ \hline \hline \end{tabular}
\end{table}
Table 6: Quantitative results for ablation study of the appearance and perceptual losses on CFEED [27].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & **FID \(\downarrow\)** & **IS \(\uparrow\)** & **SSIM \(\uparrow\)** & **PSNR \(\uparrow\)** & **MAE \(\downarrow\)** \\ \hline Model I & **20.61** & **28.14** & **0.89** & **25.76** & **1.24** \\ Model II & 21.35 & 28.09 & 0.85 & 23.92 & 1.33 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Quantitative results for ablation study of emotion inference module on CFEED [27].