This technical report presents our approach "Knights" to solve the action recognition task on a small subset of Kinetics-400 i.e. Kinetics400ViPriors without using any extra-data. Our approach has 3 main components: state-of-the-art Temporal Contrastive self-supervised pretraining, video transformer models, and optical flow modality. Along with the use of standard test-time augmentation, our proposed solution achieves 73% on Kinetics400ViPriors test set, which is the best among all of the other entries Visual Inductive Priors for Data-Efficient Computer Vision's Action Recognition Challenge, ICCV 2021.
翻译：本技术报告介绍我们的“夜间”方法,用以在不使用任何额外数据的情况下,解决一小组动因-400,即动因-400 Viprirs的动作识别任务。我们的方法有三个主要组成部分:最先进的时间对抗自我监督的训练前期、视频变压器模型和光学流模式。在使用标准测试时间增强的同时,我们提议的解决方案在动因-400 Viprirs测试集上达到了73%,这是数据-功能计算机视觉行动识别挑战(ICCV 2021)所有其他条目中最好的。
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