Neural Graph Matching Networks for Fewshot 3D Action Recognition

ECCV 2018 • Michelle Guo • Edward Chou • De-An Huang • Shuran Song • Serena Yeung • Li Fei-Fei

We propose Neural Graph Matching (NGM) Networks, a novel framework that can learn to recognize a previous unseen 3D action class with only a few examples. We achieve this by leveraging the inherent structure of 3D data through a graphical representation... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Skeleton Based Action Recognition CAD-120 NGM (5-shot) Accuracy 91.1% # 1
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Skeleton Based Action Recognition CAD-120 NGM w/o Edges (5-shot) Accuracy 85.0% # 5
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