By adding detected object nodes to skeleton graphs and training with a variable-graph network plus a random node attack regularizer, the authors report large accuracy gains over skeleton-only baselines on action recognition benchmarks.
In: ICDSMLA 2019: Proceedings of the 1st International Conference on Data Science, Machine Learning and Applications, pp
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Improving Skeleton-based Action Recognition with Interactive Object Information
By adding detected object nodes to skeleton graphs and training with a variable-graph network plus a random node attack regularizer, the authors report large accuracy gains over skeleton-only baselines on action recognition benchmarks.