In this paper we propose an approach towards this goal: We address the task of visual SRL (vSRL) and learn frame-semantic representations of images.
we present a model that learns to ground the semantic roles of a semantic frame in image regions, which may be crucial for, e.g., human-robot interaction or surveillance (e.g., Who/Where is the robber?).