To address these challenges, we propose MSCLF: A multi-subject contrastive learning framework for consistent EEG representation in stereoscopic visual discomfort detection. The framework integrates ...

Abstract: Contrastive loss and its variants are very popular for visual representation learning in an unsupervised scenario, where positive and negative pairs are produced to train a feature encoder ...