Self-supervised learning with randomized cross-sensor masked reconstruction for human activity recognition

Aleksej Logacjov, Kerstin Bach

Abstract: Highlights•New self-supervised cross-sensor learning auxiliary task (RCSMR) for HAR.•Large-scale dual-sensor pre-training, single-sensor downstream training.•RCSMR pre-trained Transformer outperforms supervised & SSL methods on 7 HAR datasets.•RCSMR has better activity separability in the latent space than other auxiliary tasks.•RCSMR is effective on limited amounts of labeled data and different model sizes.