A Baseline Framework for Part-level Action Parsing and Action Recognition

• URL: http://arxiv.org/abs/2110.03368v1
• Date: Thu, 7 Oct 2021 12:04:59 GMT
• Title: A Baseline Framework for Part-level Action Parsing and Action Recognition
• Authors: Xiaodong Chen, Xinchen Liu, Kun Liu, Wu Liu, Tao Mei
• Abstract summary: This 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. In the competition, we achieved 61.37% mAP on the test set of Kinetics-TPS.
• Score: 67.38737952295504
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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