2025
RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data
ICLR 2025poster
We present RelCon, a novel self-supervised Relative Contrastive learning approach for training a motion foundation model from wearable accelerometry sensors. First, a learnable distance measure is trained to capture motif similarity and domain-specific semantic information such as rotation invarianc…