Adaptive Stage-Aware Assessment Skill Transfer for Skill Determination

Skill determination aims to evaluate how well a participant performs a specific action. The task is rather challenging, due to the diversity of action types and the scarcity of samples. Many existing works train a skill determination model on limited samples of each action type separately. However, they neglect the skill similarities shared by different action types that can be exploited to enhance the skill determination process. How to exploit useful assessment skills from source actions to a related target action remains a challenge, and existing works have not ever found an effective way to accomplish this. In this work, we propose to achieve skill transfer for action assessment by an Ada ptive Stage-aware Assessment S kill T ransfer framework ( AdaST ) that transfers assessment skills from source actions to different stages of a target action adaptively. A source action search scheme is proposed to select relevant source actions for each target action. Furthermore, to encourage transferring effective and non-redundant assessment skills, a consistency loss and an orthogonality loss are introduced to ensure that the transferred assessment skills do not degrade the accurate determination and it provides complementary information. Extensive experiments on three public datasets demonstrate the effectiveness of the proposed method.