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Found 4 papers, 3 papers with code
Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition
One-shot action recognition allows the recognition of human-performed actions with only a single training example.
Ranked #2 on
One-Shot 3D Action Recognition
on NTU RGB+D 120
SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition
Further, we show that our approach generalizes well in experiments on the UTD-MHAD dataset for inertial, skeleton and fused data and the Simitate dataset for motion capturing data.
Ranked #3 on
One-Shot 3D Action Recognition
on NTU RGB+D 120
Gimme Signals: Discriminative signal encoding for multimodal activity recognition
We present a simple, yet effective and flexible method for action recognition supporting multiple sensor modalities.
Ranked #2 on
Multimodal Activity Recognition
on UTD-MHAD
Markerless Visual Robot Programming by Demonstration
We analyze a set of spatial constraints on human pose data extracted using convolutional pose machines and object informations extracted from 2D image sequences.
