3 ms·

I think faces are much easier than reflections for a few reasons. 1. faces aren't perfectly symmetric. There is a bunch of leeway on the small scale 2. faces

I think faces are much easier than reflections for a few reasons. 1. faces aren't perfectly symmetric. There is a bunch of leeway on the small scale 2. faces can be oriented to make lack of symmetry harder to see (most photos aren't people perfectly facing the camera) 3. faces can be parametrized with relatively few parameters. You need correct position and sizing for eyes, nose, mouth, eyebrows and ears. If you get those right, everything else is doable based only on local information. For a mountain range reflection, you need to transfer a ton of exact information across the image (and that information can't easily be embedded in 2d. to know the reflection, you have to have a 3d map).

notahacker 4y ago
Eyeballs appearing to point in different directions and really asymmetric ears are among the common 'tells' of AI generation in a lot of models too. I think the biggest challenge is that unlike facial symmetry, reflected mountains in training sets are often significantly perturbed by ripples and objects in the water. So tones in the water broadly matching the tones of the mountains above but with different texture is "good enough" for the model, and it doesn't catch finer detail mismatches in shapes of edges in the same way it catches finer detail mismatches in the shapes of eyes, which almost invariably have the same texture and similar lighting to their compatriot in images.