In novel Deep Learning applications, complex models and algorithms are designed to understand the world around us. Every scene we see in real life can be represented as a set of objects and a set of predicates (actions, prepositions, etc.). Starting from these sets, a graph can be defined with objects as nodes and predicates as links. Every relationship between two objects is a triplet (subject, predicate, object). This task is called scene graph generation and it is divided into two phases: first, locate objects and predict their classes (object detection), then create the set of possible triplets (relationship detection). In the last years, this topic has gained considered attention by the research community as it is part of more challenging machine learning problems.