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Computer Science > Computer Vision and Pattern Recognition

arXiv:2305.11675 (cs)
[Submitted on 19 May 2023]

Title:Cinematic Mindscapes: High-quality Video Reconstruction from
Brain Activity

Authors:Zijiao Chen, Jiaxin Qing, Juan Helen Zhou
Download a PDF of the paper titled Cinematic Mindscapes: High-quality
Video Reconstruction from Brain Activity, by Zijiao Chen and 2 other
authors
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    Abstract: Reconstructing human vision from brain activities has
    been an appealing task that helps to understand our cognitive
    process. Even though recent research has seen great success in
    reconstructing static images from non-invasive brain recordings,
    work on recovering continuous visual experiences in the form of
    videos is limited. In this work, we propose Mind-Video that
    learns spatiotemporal information from continuous fMRI data of
    the cerebral cortex progressively through masked brain modeling,
    multimodal contrastive learning with spatiotemporal attention,
    and co-training with an augmented Stable Diffusion model that
    incorporates network temporal inflation. We show that
    high-quality videos of arbitrary frame rates can be reconstructed
    with Mind-Video using adversarial guidance. The recovered videos
    were evaluated with various semantic and pixel-level metrics. We
    achieved an average accuracy of 85% in semantic classification
    tasks and 0.19 in structural similarity index (SSIM),
    outperforming the previous state-of-the-art by 45%. We also show
    that our model is biologically plausible and interpretable,
    reflecting established physiological processes.

Comments: 15 pages, 11 figures, submitted to anonymous conference
Subjects: Computer Vision and Pattern Recognition (cs.CV);
          Computational Engineering, Finance, and Science (cs.CE)
Cite as:  arXiv:2305.11675 [cs.CV]
          (or arXiv:2305.11675v1 [cs.CV] for this version)
          https://doi.org/10.48550/arXiv.2305.11675
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Zijiao Chen [view email]
[v1] Fri, 19 May 2023 13:44:25 UTC (21,945 KB)
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