Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

ArXi:2604.10344v1 Announce Type: new The classical approach to detecting depression from vision emphasizes interpretable features, such as facial expression, and classifiers such as the Vector Machine (SVM). With the advent of deep learning, there has been a shift in feature representations and classification approaches. Contemporary approaches use learnt features from general-purpose vision models such as VGGNet to train machine learning models.