I immediately found the results suspect, and think I have found what is actually going on. The dataset it was trained on was 2770 images, minus 982 of those used for validation. I posit that the system did not actually read any pictures from the brains, but simply overfitted all the training images into the network itself. For example, if one looks at a picture of a teddy bear, you'd get an overfitted picture of anot…
High-res image reconstruction with latent diffusion models from human brain
21–30 of 170 posts
Re: High-res image reconstruction with latent diffusion models from human brain
#22Earlier quoted context omitted.
The end game here is developing a mind reading device. The endeavor device is ethically questionable because such a device would have a lot of ethically wrong/questionable applications.
The only thing that's ethically questionable are humans themselves and such a device would likely do more to expose the unethical. Everybody remembers what happen when online dna hit mainstream.
Re: High-res image reconstruction with latent diffusion models from human brain
#23Re: High-res image reconstruction with latent diffusion models from human brain
#24I am suspicious of these results; if we blast a high frequency visual stimulus of a couple of letters and do quite a lot of post processing we can sometimes get a visual cortex map of those particular letters. However, these paper examples are very complex images and I’m very doubtful of the results - aransentin above made a couple of very valid points
I could imagine improvements since then,especially with advances in image networks.
Re: High-res image reconstruction with latent diffusion models from human brain
#25My understanding is that we won’t get a “mind reader” model out of this, because visual stimulus vs your imagination happen in separate parts of the brain. In other words we won’t be reading the minds of suspected criminals anytime soon. Maybe someone with neurology experience can chime in here? Is it even theoretically possible to see what’s happening in the imagination?
Re: High-res image reconstruction with latent diffusion models from human brain
#26I immediately found the results suspect, and think I have found what is actually going on. The dataset it was trained on was 2770 images, minus 982 of those used for validation. I posit that the system did not actually read any pictures from the brains, but simply overfitted all the training images into the network itself. For example, if one looks at a picture of a teddy bear, you'd get an overfitted picture of anot…
Re: High-res image reconstruction with latent diffusion models from human brain
#27I immediately found the results suspect, and think I have found what is actually going on. The dataset it was trained on was 2770 images, minus 982 of those used for validation. I posit that the system did not actually read any pictures from the brains, but simply overfitted all the training images into the network itself. For example, if one looks at a picture of a teddy bear, you'd get an overfitted picture of anot…
Re: High-res image reconstruction with latent diffusion models from human brain
#28I immediately found the results suspect, and think I have found what is actually going on. The dataset it was trained on was 2770 images, minus 982 of those used for validation. I posit that the system did not actually read any pictures from the brains, but simply overfitted all the training images into the network itself. For example, if one looks at a picture of a teddy bear, you'd get an overfitted picture of anot…
Re: High-res image reconstruction with latent diffusion models from human brain
#29The human mind is considered the only place where we have true privacy. All these efforts are taking that away.
At this rate all notions of privacy will soon be dead.
Re: High-res image reconstruction with latent diffusion models from human brain
#30I immediately found the results suspect, and think I have found what is actually going on. The dataset it was trained on was 2770 images, minus 982 of those used for validation. I posit that the system did not actually read any pictures from the brains, but simply overfitted all the training images into the network itself. For example, if one looks at a picture of a teddy bear, you'd get an overfitted picture of anot…