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2026-07-24 00:00 Papers Sensation & Feedback Translated from EN

fMRI2Face Reconstructs Dynamic Faces From Brain Activity

Summary An arXiv preprint introduces fMRI-Face, a Full-HD fMRI-video dataset, and fMRI2Face, a geometry-guided framework for reconstructing dynamic faces from brain activity. The method combines brain-derived appearance context with morphable 3D facial control in a neural-controlled video-diffusion pipeline. The work has not been peer reviewed.
Why it matters The release contributes both a dataset and a decoding framework to an emerging area of dynamic visual reconstruction from fMRI.

BCIwiki (bciwiki.com) — Researchers report that fMRI2Face, a geometry-guided neural decoding framework, enables high-fidelity facial video reconstruction directly from brain activity, according to a preprint posted to arXiv on July 24, 2026 that has not yet undergone peer review.

The study introduces fMRI-Face, a Full-HD fMRI-video dataset, and fMRI2Face, a geometry-guided neural decoding framework for dynamic human face reconstruction. fMRI2Face derives two complementary neural controls from brain activity, Brain-derived Appearance Context and Morphable 3D Facial Control, and integrates them through Neural-Controlled Video Diffusion with auxiliary latent completion, enabling high-fidelity facial video reconstruction directly from brain activity.

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Sources · 1
arxiv.org 2026-07-24
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