This technical report introduces our 2nd place solution to Kinetics-TPS Track on Part-level Action Parsing in ICCV DeeperAction Workshop 2021. Our entry is mainly based on YOLOF for instance and part detection, HRNet for human pose estimation, and CSN for video-level action recognition and frame-level part state parsing. We describe technical details for the Kinetics-TPS dataset, together with some experimental results. In the competition, we achieved 61.37% mAP on the test set of Kinetics-TPS.

翻译：本技术报告介绍了我们在国际电算学会深层行动讲习班2021年关于部分行动分析的动因-TPS轨道上的第二位解决办法。我们的条目主要基于例如“YOLOF”和“部分探测”、“人姿估计的HRNet”和“视频行动识别”和“框架级部分状态分析”。我们描述了动因-TPS数据集的技术细节以及一些实验结果。在竞赛中,我们在“动因-TPS”测试组上取得了61.37%的MAP。