An Audio-Video Deep and Transfer Learning Framework for Multimodal Emotion Recognition in the wild

In this paper, we present our contribution to ABAW facial expression challenge. We report the proposed system and the official challenge results adhering to the challenge protocol. Using end-to-end deep learning and benefiting from transfer learning approaches, we reached a test set challenge performance measure of 42.10%.
Comment: Results on test dataset and acknowledgements were added