[2508.20765] Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding

Computer Science > Computer Vision and Pattern Recognition arXiv:2508.20765 (cs) [Submitted on 28 Aug 2025 (v1), last revised 8 Apr 2026 (this version, v2)] Title:Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding Authors:Gowreesh Mago, Pascal Mettes, Stevan Rudinac View a PDF of the paper titled Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding, by Gowreesh Mago and 2 other authors View PDF HTML (experimental) Abstract:The automatic understanding of video content is advancing rapidly. Empowered by deeper neural networks and large datasets, machines are increasingly capable of understanding what is concretely visible in video frames, whether it be objects, actions, events, or scenes. In comparison, humans retain a unique ability to also look beyond concrete entities and recognize abstract concepts like justice, freedom, and togetherness. Abstract concept recognition forms a crucial open challenge in video understanding, where reasoning on multiple semantic levels based on contextual information is key. In this paper, we argue that the recent advances in foundation models make for an ideal setting to address abstract concept understanding in videos. Automated understanding of high-level abstract concepts is imperative as it enables models to be more aligned with human reasoning and values. In this survey, we study different tasks and datasets used to understand abstract concepts in video co...