Expression Representation

Expression representation research focuses on developing effective methods to capture and encode facial expressions and emotions for applications like facial expression recognition and emotion analysis. Current research emphasizes improving the generalizability of models across diverse datasets, often employing deep metric learning with novel loss functions and architectures like multi-threshold approaches or contrastive learning, and exploring the use of 3D facial shape information alongside 2D image data. These advancements aim to create more robust and accurate systems for understanding human affect, with implications for fields ranging from human-computer interaction to mental health assessment.