Re:Perceptual Image Codec: What Matters in Practical Learned...
by srean on Sunday May 24, 2026 @12:54PM
(#48258915)
This is a potential problem in "AI" denoising as well.
These denoising models, the autoencoders more directly so, work by (lossily) mapping the raw input to a very low dimensional representation. The other part generates the desired image back from the low-d representation.
The problem is that nothing, in the vanilla versions, prevent the the low-d version to be a semantics representation such as, Moon, dark hair etc and the generative part to take cues from the semantic representation to a generated sub-image.
The Samsung phone Moon image was likely a result of deliberate choice / company policy, but these things can happen without explicit intent.
These denoising models, the autoencoders more directly so, work by (lossily) mapping the raw input to a very low dimensional representation. The other part generates the desired image back from the low-d representation.
The problem is that nothing, in the vanilla versions, prevent the the low-d version to be a semantics representation such as, Moon, dark hair etc and the generative part to take cues from the semantic representation to a generated sub-image.
The Samsung phone Moon image was likely a result of deliberate choice / company policy, but these things can happen without explicit intent.