CVDII: Enhancing One-Shot Skeleton Action Recognition Through Cross-View Dynamic Information Interaction

One-shot 3D skeleton action recognition task struggles with diverse intra-class action execution styles, causing excessive discriminative information to obstruct obtaining separable feature space. We innovatively propose leveraging shared information among intra-class action executions to mitigate the over-influence of discriminative information. To this end, we proposed dynamic information interaction module (DIIM) that enables shared information to effectively weaken excessive discriminative information. Specifically, DIIM facilitates effective information interaction by constructing a guided evolution pool to store execution-related shared information and ensure such information can be retrieved. We devise shared-discriminative projection strategy (SDPS) which adopts different feature extraction strategies for specific skeleton topologies to target mining discriminative and shared information from different views of skeleton data. In summary, our proposed Cross-View Dynamic Information Interaction (CVDII) framework integrates DIIM and SDPS, effectively tackles the problem of discriminative information redundancy caused by diverse intra-class action execution styles. Experiments conducted on NTU 60, NTU 120, PKU-MMD, and Kinetics datasets demonstrate that our proposed CVDII achieves remarkable performance.