论文标题
视频动作识别方法的准确性和性能比较
Accuracy and Performance Comparison of Video Action Recognition Approaches
论文作者
论文摘要
在过去的几年中，人们对视频行动识别系统和模型一直引起了浓厚的兴趣。但是，通过不同的训练环境，硬件规格，超参数，管道和推理方法，直接比较准确性和计算性能结果仍然笼罩了云。本文通过确保这些培训特征的一致性，为读者提供了不同类型的视频动作识别算法的有意义的比较，从而提供了14个现成模型和最先进模型之间的直接比较。除了提出的新精确度指标外，还使用标准TOP-1和TOP-5精度指标评估模型的精度。此外，我们比较了最先进的HPC系统中分布式培训的计算性能。
Over the past few years, there has been significant interest in video action recognition systems and models. However, direct comparison of accuracy and computational performance results remain clouded by differing training environments, hardware specifications, hyperparameters, pipelines, and inference methods. This article provides a direct comparison between fourteen off-the-shelf and state-of-the-art models by ensuring consistency in these training characteristics in order to provide readers with a meaningful comparison across different types of video action recognition algorithms. Accuracy of the models is evaluated using standard Top-1 and Top-5 accuracy metrics in addition to a proposed new accuracy metric. Additionally, we compare computational performance of distributed training from two to sixty-four GPUs on a state-of-the-art HPC system.
