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Brain-to-Image Generation: Reconstructing Visual Stimuli from EEG using Generative Adversarial Networks
Author 1, Author 2, Author 3, Author 4, Author 5
generative modelsEEGimage reconstructionsemantic decoding
2609.22282
Builder Relevance
4h ago60%
Abstract
This paper explores the reconstruction of visual stimuli from EEG data using generative models, achieving above-chance semantic decoding.
Reality Card
Core Claim
The model demonstrates the ability to retrieve visual stimuli in a visual embedding space with image recall rates significantly above chance levels.
Method / Result
Achieved 58.00 +/- 1.73% image recall at rank 10.
Limitations
Performance drops significantly when applying the model to subjects other than the one it was trained on, indicating subject specificity.
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