Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning

Understand

Reconstructing visual stimulus (image) only from human brain activity measured with functional Magnetic Resonance Imaging (fMRI) is a significant and meaningful task in Human-AI collaboration.

• However, the inconsistent distribution and representation between fMRI signals and visual images cause the heterogeneity gap.
• Moreover, the fMRI data is often extremely high-dimensional and contains a lot of visually-irrelevant information.
• Existing methods generally suffer from these issues so that a satisfactory reconstruction is still challenging.