MindCross: Fast New Subject Adaptation with Limited Data for Cross-subject Video Reconstruction from Brain Signals
Xuan-Hao Liu, Yan-Kai Liu, Tianyi Zhou, Bao-Liang Lu, Wei-Long Zheng
Abstract
Brain decoding aims to reconstruct video from brain signals. Existing brain decoding frameworks are primarily built on a subject-dependent paradigm, which requires large amounts of brain data for each subject. However, the expensive cost of collecting brain-video data causes severe data scarcity for brain decoding. Although some cross-subject methods being introduced, they often exhibit an excessive preoccupation with subject-invariant information while neglecting subject-specific information, resulting in slow fine-tune-based adaptation strategy. To achieve fast and data-efficient new subject adaptation, we propose **MindCross**, a novel cross-subject brain decoding framework. MindCross
BibTeX
@inproceedings{aaai2026_mindcrossfastnew,
title = {MindCross: Fast New Subject Adaptation with Limited Data for Cross-subject Video Reconstruction from Brain Signals},
author = {Xuan-Hao Liu and Yan-Kai Liu and Tianyi Zhou and Bao-Liang Lu and Wei-Long Zheng},
booktitle = {AAAI 2026},
year = {2026}
}