  In this report we describe the technical details of our submission to the
EPIC-Kitchens 2019 action recognition challenge. To participate in the
challenge we have developed a number of CNN-LSTA [3] and HF-TSN [2] variants,
and submitted predictions from an ensemble compiled out of these two model
families. Our submission, visible on the public leaderboard with team name
FBK-HUPBA, achieved a top-1 action recognition accuracy of 35.54% on S1
setting, and 20.25% on S2 setting.
