论文标题
2019年时代挑战赛的多毛线挑战的顶级解决方案
Top-1 Solution of Multi-Moments in Time Challenge 2019
论文作者
论文摘要
在这份技术报告中，我们简要介绍了ICCV 2019中的多余时间挑战的团队“有效”的解决方案。我们首先通过流行的基于图像的动作识别方法TRN，TSN和TSM进行了几项实验。然后提出了一个新型的时间交织网络，以快速准确地识别。此外，探索了慢速网络及其变体。最后，我们整合了上述所有模型，并在验证集上实现67.22 \％，在测试集中为60.77 \％，在最终排行榜上排名第一。此外，我们发布了一个新的代码存储库，以供视频理解，该存储库统一了基于Pytorch的最新2D和3D方法。挑战的解决方案还包括在https://github.com/sense-x/x-temporal中的存储库中。
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.
