If you refuse their tracking and marketing cookies it redirects you to google.com. Classy.
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AI real-time human full-body photo generator
161–170 of 421 posts
Re: AI real-time human full-body photo generator
#162Earlier quoted context omitted.
Looking at the poses, it feels optimized for generating porn, but one example someone showed had a child's face (good god please don't let your "AI" system generate child anything if you want to sell it for porn purposes), and another user noted that their attempt error'd out because it "detected nudity", even though other users get given a nude model by default.
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Re: AI real-time human full-body photo generator
#163Why is it impossible to generate a male model wearing anything other than rolled denim jean shorts? I've tried things like "long pants" or "ankle-length pants," but I cannot get it to stop putting them all in denim shorts!
I got one with regular shorts: https://generated.photos/human-generator/64e67772190809000bb...
I don’t understand why none of these generators want to make a man with body hair. I specified Armenian and Armenians are notoriously hairy.
Edit: this is if I specify “very hairy”. Note that for a man, there is a bit of hair in the usual places but still far short of “very hairy” IMO. https://generated.photos/human-generator/64e67aa38448b800095... (And the hair rendering is bad, AI still doesn’t understand directionality; there’s a very common pattern it should know, especially on the chest)
Re: AI real-time human full-body photo generator
#164If you refuse their tracking and marketing cookies it redirects you to google.com. Classy.
I'm surprised browsers don't offer something like Docker so that each site is isolated to its own virtual environment.
Chrome profiles work exactly like this, you can set up any number of profiles and they all have their own configuration/sessions etc.
I use home and work profiles on my laptop for instance, works really well.
Re: AI real-time human full-body photo generator
#165What would a company do with 10,000 photorealistic photos of an AI generated human... per month?
Re: AI real-time human full-body photo generator
#166If you're wondering how it's so fast and cheap and they can generate variants so easily, it's because they're using GANs (see the footer). GANs are way faster than diffusion models because they generate the image in a single forward pass and their true latent space encoding makes editing a breeze. (And if you're wondering how it can look so good when 'everyone knows GANs don't work because they're too unstable', a wi…
>And if you're wondering how it can look so good
I don't think anyone is wondering this, especially if they are used to playing with diffusion models.
Re: AI real-time human full-body photo generator
#167Neat. I'd really like to have a setting for attractiveness, all of these people look like models.
Re: AI real-time human full-body photo generator
#168What would a company do with 10,000 photorealistic photos of an AI generated human... per month?
On-demand generation of NPCs for video games? Or background extras in movies?
Or maybe a people trying clothes on virtually.
Re: AI real-time human full-body photo generator
#169Accuracy on using an existing face seems pretty off. Certain positions have terrible accuracy on body parts. Why would you care to use this again? This just seems like another AI SaaS scam project where they're basically charging others to use their A100s with their copy-pasted implemented version of the research paper algorithms. These should just all be outlawed IMO.
Re: AI real-time human full-body photo generator
#170Earlier quoted context omitted.
You’re overstating the simplicity of a scaling a GAN well. GigaGAN is the best quality out of those and requires 7 loss functions and is incredibly complicated. Sure GANs can scale, but Diffusion models are drastically easier to scale.
No, I'm not. BigGAN did fine on scaling up to JFT-300M with basically no changes beyond model size and a simple architecture. This is also what we were observing, even with a buggy BigGAN implementation. GigaGAN is the best quality, but that's mostly because it's also the biggest; as Table 1 shows most of the gains come from various kinds of additional scaling. (And this is moving the goalposts from the usual asserti…
Researchers have spent several years try to even create a GAN that can fit well a distribution made of aligned faces (resulted into StyleGAN1/2); with a simple unet with e-objective and cosine schedule you can fit much complex distributions, still using one loss: L1/L2.
Reading your comments make me feel like that you believe that just every researchers (even extremely smart dude like Karras) just switch to diffusion models because they are idiots, they should have instead focus on GANs and today we will have GANs that are as powerful or more than the diffusion models we have today and also work one step; this is just a weird delusion. Diffusion models are just simply much easier to train (just a L1/L2 loss in most cases), write (for example your buggy BigGAN implementation), they usually work out-of-box on different resolutions and aspect ratios, you can just finetune them if you want to create an inpainting model; and for what is right now you just need much less compute to reach a good image coherency or maybe just reaching a coherence that as not been achieved by GAN models; like I would be curious even on a small scale experiment what a GAN (with ~55M parameters) would be able to perform after a 1-day/2-day GPU time of training on Icon645 dataset, because my diffusion model I can assure is much better than I could have imagine while being trivial to implement (I just implemented a Unet as I remember one, nothing rigorous and of course no architecture sweep).