  In this technical report, we briefly introduce the solutions of our team
'Efficient' for the Multi-Moments in Time challenge in ICCV 2019. We first
conduct several experiments with popular Image-Based action recognition methods
TRN, TSN, and TSM. Then a novel temporal interlacing network is proposed
towards fast and accurate recognition. Besides, the SlowFast network and its
variants are explored. Finally, we ensemble all the above models and achieve
67.22\% on the validation set and 60.77\% on the test set, which ranks 1st on
the final leaderboard. In addition, we release a new code repository for video
understanding which unifies state-of-the-art 2D and 3D methods based on
PyTorch. The solution of the challenge is also included in the repository,
which is available at https://github.com/Sense-X/X-Temporal.
