  Research in action detection has grown in the recentyears, as it plays a key
role in video understanding. Modelling the interactions (either spatial or
temporal) between actors and their context has proven to be essential for this
task. While recent works use spatial features with aggregated temporal
information, this work proposes to use non-aggregated temporal information.
This is done by adding an attention based method that leverages spatio-temporal
interactions between elements in the scene along the clip.The main contribution
of this work is the introduction of two cross attention blocks to effectively
model the spatial relations and capture short range temporal
interactions.Experiments on the AVA dataset show the advantages of the proposed
approach that models spatio-temporal relations between relevant elements in the
scene, outperforming other methods that model actor interactions with their
context by +0.31 mAP.
