Physical-aware Cross-modal Adversarial Network for Wearable Sensor-based Human Action Recognition

Understand

Wearable sensor-based Human Action Recognition (HAR) has made significant strides in recent times.

• However, the accuracy performance of wearable sensor-based HAR is currently still lagging behind that of visual modalities-based systems, such as RGB video and depth data.
• Although diverse input modalities can provide complementary cues and improve the accuracy performance of HAR, wearable devices can only capture limited kinds of non-visual time series input, such as accelerometers and gyroscopes.
• This limitation hinders the deployment of multimodal simultaneously using visual and non-visual modality data in parallel on current wearable devices.