Brain-based image retrieval can work for new users without retraining by learning to recover the geometric transformation between their brain's coordinate system and a shared visual space, using only unlabeled test-time alignment.
This paper tackles cross-subject EEG-to-image retrieval—retrieving images that match brain signals from new users without labeled training data. The key insight is that different people's brains organize visual concepts similarly but along different coordinate directions.