Mind-Video

Mind-Video

Decoding Brain Activity to Visual Experiences

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Mind-Video is an AI tool that focuses on high-quality video reconstruction from brain activity data obtained through fMRI scans. The tool aims to bridge the gap between image and video brain decoding by leveraging masked brain modeling, multimodal contrastive learning, spatiotemporal attention, and co-training with an augmented Stable Diffusion model. It is designed to enhance the generation consistency and accuracy of reconstructing continuous visual experiences from brain activities, ultimately contributing to a deeper understanding of human cognitive processes.

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Features

Advantages

  • Bridges the gap between image and video brain decoding
  • Enhances generation consistency and accuracy
  • Reconstructs continuous visual experiences from brain activities
  • Achieves high accuracy in semantic and pixel metrics
  • Provides biologically plausible and interpretable results

Disadvantages

  • Lack of pixel-level controllability in generation process
  • Uncontrollable factors like mind wandering during fMRI scans
  • Potential mismatch between ground truth and generated results

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