EVA-Net improves subject-independent EEG motor decoding by using video action priors via cross-modal contrastive alignment and knowledge distillation, reporting an 8.66% LOSO accuracy gain on EEGMMI.
arXiv:2507.02320 (2025).https://arxiv.org/abs/2507.02320
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EVA-Net: Subject-Independent EEG Motor Decoding with Video-Derived Motor Priors
EVA-Net improves subject-independent EEG motor decoding by using video action priors via cross-modal contrastive alignment and knowledge distillation, reporting an 8.66% LOSO accuracy gain on EEGMMI.