# Guided Spatial Transformers for Facial Expression Recognition
## 6 Conclusions
In future versions, we will consider these sources of error to reduce their contribution to the recognition rate. Other sources of errors in our models come from the distinction between emotions, as in 'Happy' and 'Contempt'. They share similar patterns but their valences are opposed. For these cases, one solution will be to evaluate models with higher resolution imagesat their input, or to train customized models to distinguish between these 2 emotions to reduce the confusion between them. As future lines, we also plan to apply these strategies to other fields to confirm the generalization capacity of these solutions. Additionally, we will study the possibility of developing different Spatial Transformers to focus on the eyes, nose, and mouth to extract information from each region and combine them in a posterior step. Furthermore, we reckon on exploring architectures with more layers to see if the network still benefits from the attention mechanism or not. Finally, we will extend our study to improve the landmark solutions when the face is not detected. Conceptualization, C.L.-J., R.K., M.G.-M. and F.F.-M.; Data curation, [PERSON]-J., [PERSON]-M. and R.K.; Formal analysis, [PERSON]-J. and [PERSON]-M.; Funding acquisition, M.G.-M., J.M.M. and F.F.-M.; Investigation, [PERSON]-J., [PERSON]-M., R.K. and F.F.-M.; Methodology, [PERSON]-J., [PERSON]-M., R.K. and F.F.-M.; Project administration, M.G.-M., J.M.M. and F.F.-M.; Resources, M.G.-M. and F.F.-M.; Software, [PERSON]-J. and [PERSON]-M. and R.K.; Supervision, M.G.-M., J.M.M. and F.F.-M.; Validation, [PERSON] and [PERSON]; Visualization, [PERSON] and [PERSON]; Writing--original draft, [PERSON] and [PERSON]; Writing--review and editing, [PERSON], R.K. and [PERSON]. All authors have read and agreed to the published version of the manuscript. The work leading to these results has been supported by the Spanish Ministry of Economy, Industry and Competitiveness through the CAVIAR (MINECO, TEC2017-84593-C2-1-R) and AMIC (MINECO, TIN2017-85854-C4-4-R) projects (AEI/FEDER, UE). Also, R.K.'s research was supported by the Spanish Ministry of Education (FPI grant PRE2018-083225). Ethical review and approval were waived for this study, because the datasets used are accessible under request for research purposes or open-accessed under 'Open Database License' and the authors of this work were adhered to the terms of the license agreement of the first dataset. Subject consent was waived because the datasets used are accessible under request for research purposes or open-accessed under 'Open Database License' and the authors of this study were adhered to the terms of the license agreement of the datasets. All the code implemented for this publication is available at [[https://github.com/cristianlunaj/Guided-EMO-SpatialTransformer](https://github.com/cristianlunaj/Guided-EMO-SpatialTransformer)]([https://github.com/cristianlunaj/Guided-EMO-SpatialTransformer](https://github.com/cristianlunaj/Guided-EMO-SpatialTransformer)), accessed on 2 August 2021. The AffectNet database used in this paper is available under request from [[http://mohammadmahoor.com/affectnet/](http://mohammadmahoor.com/affectnet/)]([http://mohammadmahoor.com/affectnet/](http://mohammadmahoor.com/affectnet/)), accessed on 27 July 2021. This database is available only for research and educational purpose and not for any commercial use. FER-2013 is open-access and can be downloaded from [[https://www.kaggle.com/msambare/fer2013](https://www.kaggle.com/msambare/fer2013)]([https://www.kaggle.com/msambare/fer2013](https://www.kaggle.com/msambare/fer2013)), accessed on 27 July 2021. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan X Pascal GPU used for part of this research. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: