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> Second, we need the ability to persist a design. I See yesterday's Stable Diffusion article: https://news.ycombinator.com/item?id=32643564 https://news.ycomb

> Second, we need the ability to persist a design. I See yesterday's Stable Diffusion article: https://news.ycombinator.com/item?id=32643564 https://news.ycombinator.com/item?id=32643564

michaelchisari 4y ago
I haven't had a chance to try it yet, I'm optimistic but skeptical that it can have true persistence like I'm referring to. Especially since it requires training your own model which requires multiple images of the same asset/character/object/etc.
- deleted 4y ago
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- nomel 4y ago
  For what I think you have in mind, I suspect it will eventually not be "image to image", but "<ai thing> to <ai thing> + image", for that guess to be remotely repeatable. That "ai thing" is probably the persistence you're talking about. I think that thing will neccesarily contained representations of dimension, behavior (physics/bones), and "style". Without the "ai thing", if only using an image/text, the character would have to be impossibly represented in the model, so it could guess all of these things predictably. For example, what that character looks like from a side profile, or behind. What if it's an alien, and its arms should always bend backwards? Could a text representation ever be made to completely describe this, with good reproducibility? Probably not. But, I assume some non-human representation would have a better chance. As is, if something known is required, I think the behavior of these models can be considered "destructive" to the input image, more often than not. For this reason, I think artists are safe, for the time being. :)
- Filligree 4y ago
  Textual inversion seems like it'll eventually cover this space. But bootstrapping is going to be harder than necessary, yes.
isaacfrond 4y ago
For face generation, I think there are deep neural networks that can generate multiple views of the same face [1], [2]. Stable diffusion already provides the possibility to generate variations. So I don't think it is a stretch to imagine that these existing capabilities will only get better and/or be applied to SD. [1]: Multi-View 3D Face Reconstruction with Deep Recurrent Neural Networks [2]: Deep Neural Network Augmentation: Generating Faces for Affect Analysis

> Second, we need the ability to persist a design. I See yesterday's Stable Diffusion article: https://news.ycombinator.com/item?id=32643564 https://news.ycombinator.com/item?id=32643564

michaelchisari 4y ago

I haven't had a chance to try it yet, I'm optimistic but skeptical that it can have true persistence like I'm referring to. Especially since it requires training your own model which requires multiple images of the same asset/character/object/etc.

deleted 4y ago
[deleted]
nomel 4y ago
For what I think you have in mind, I suspect it will eventually not be "image to image", but "<ai thing> to <ai thing> + image", for that guess to be remotely repeatable. That "ai thing" is probably the persistence you're talking about. I think that thing will neccesarily contained representations of dimension, behavior (physics/bones), and "style". Without the "ai thing", if only using an image/text, the character would have to be impossibly represented in the model, so it could guess all of these things predictably. For example, what that character looks like from a side profile, or behind. What if it's an alien, and its arms should always bend backwards? Could a text representation ever be made to completely describe this, with good reproducibility? Probably not. But, I assume some non-human representation would have a better chance. As is, if something known is required, I think the behavior of these models can be considered "destructive" to the input image, more often than not. For this reason, I think artists are safe, for the time being. :)
Filligree 4y ago
Textual inversion seems like it'll eventually cover this space. But bootstrapping is going to be harder than necessary, yes.

isaacfrond 4y ago

For face generation, I think there are deep neural networks that can generate multiple views of the same face [1], [2]. Stable diffusion already provides the possibility to generate variations. So I don't think it is a stretch to imagine that these existing capabilities will only get better and/or be applied to SD. [1]: Multi-View 3D Face Reconstruction with Deep Recurrent Neural Networks [2]: Deep Neural Network Augmentation: Generating Faces for Affect Analysis