MindTuner: Cross-Subject Visual Decoding with Visual Fingerprint and Semantic Correction

arXiv:2404.12630v1 Announce Type: new
Abstract: Decoding natural visual scenes from brain activity has flourished, with extensive research in single-subject tasks and, however, less in cross-subject tasks. Reconstructing high-quality images in cross-subject tasks is a challenging problem due to profound individual differences between subjects and the scarcity of data annotation. In this work, we proposed MindTuner for cross-subject visual decoding, which achieves high-quality and rich-semantic reconstructions using only 1 hour of fMRI training data benefiting from the phenomena of visual fingerprint …

abstract annotation arxiv brain brain activity cs.cv cs.mm data data annotation decoding differences however images natural quality research semantic tasks type visual