抄録
Early detection of depressive episodes is crucial in managing mental health disorders such as Major Depressive Disorder (MDD) and Bipolar Disorder. However, existing methods often necessitate active participation or are confined to clinical settings. While facial expressions have shown promise in laboratory settings for identifying depression, their potential in real-world applications remains largely unexplored. In this challenge we introduce a data collected state of the art facial behavior sensing system, that tracks different facial behavior primitives such as Action Units, Landmarks, Head Pose, Eye Open state and others for task of detecting depressive episode in the wild. The challenge duration was three months, from Dec 12, 2024 to Feb 28, 2025 and 8 teams participanted. Among the final teams, Team Persistence (Team ID 160) achieved 0.77 AUROC for universal model and 0.88 AUROC for hybrid model and became the winner.
https://ror.org/03czfpz43 
