  From object segmentation to word vector representations, Scene Graph
Generation (SGG) became a complex task built upon numerous research results. In
this paper, we focus on the last module of this model: the fusion function. The
role of this latter is to combine three hidden states. We perform an ablation
test in order to compare different implementations. First, we reproduce the
state-of-the-art results using SUM, and GATE functions. Then we expand the
original solution by adding more model-agnostic functions: an adapted version
of DIST and a mixture between MFB and GATE. On the basis of the
state-of-the-art configuration, DIST performed the best Recall @ K, which makes
it now part of the state-of-the-art.
