Paper Title
Face Emotion Recognition from Videos Using CNN And Transformer Models

Abstract - Detecting emotion in images or videos has grown popular due to the importance of movements and facial expressions in communicating emotion. In this proposed work, facial expressions are taken into consideration, which is based on the expression of several facial characteristics and combined to generate a simple emotion. Many alternative ways have been proposed by researchers to analyze the emotions that individuals exhibit through writing, speech, gestures, and facial expressions. This research explores a transformer-based -visual emotion identification system to overcome these issues. Work is based on validating the RAVEDESS dataset on the SWIN transformer and CNN models. There is a double-fold increase in accuracy value using a SWIN transformer compared to the best of the CNN model VGG16. Keywords - Emotion Recognition, Deep Learning, VGG16, SWIN Transformers