CM-MAE: A Physics-Guided Cross-Modal Self-Supervised Learning Framework for Vision-Wireless Applications
CM-MAE is presented, a self-supervised vision--wireless pretraining framework for cross-scenario representation transfer that builds a target distribution from similarities between measured beam-power profiles, so nonidentical samples with similar directional responses are not forced apart as false negatives.