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SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

snap-research.github.io

31–40 of 54 posts

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#31
post #29

Earlier quoted context omitted.

The phone is in airplane mode

The issue is that it’s a controlled video from the author. I can still get Wi-Fi and Bluetooth in airplane mode so the airplane mode sign isn’t “proof” enough for me to accept the paper conclusions. I hope it’s real, but posting a YouTube to assuage the “show me the implementation” isn’t going to help with my cynicism.

They clearly are not connected to WiFi. You’re concocting a pretty far fetched theory at this point.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#32
post #23

Earlier quoted context omitted.

I'll believe thier hypothesis when I can run the open source code on my iPhone in 2 seconds, doubt it's that fast.

They included a video: https://www.youtube.com/watch?v=zK5PQ3Oj_L8

How do we know the video isn't ai generated? (fnord)

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#33
post #29

Earlier quoted context omitted.

The phone is in airplane mode

The issue is that it’s a controlled video from the author. I can still get Wi-Fi and Bluetooth in airplane mode so the airplane mode sign isn’t “proof” enough for me to accept the paper conclusions. I hope it’s real, but posting a YouTube to assuage the “show me the implementation” isn’t going to help with my cynicism.

The paper describes the implementation including a detailed breakdown of the optimisation algorithm itself. It's also plausible an iPhone 14 Pro could do it given its memory b/w, ops/s and that it can fit the SD model in RAM.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#34
post #29

Earlier quoted context omitted.

The issue is that it’s a controlled video from the author. I can still get Wi-Fi and Bluetooth in airplane mode so the airplane mode sign isn’t “proof” enough for me to accept the paper conclusions. I hope it’s real, but posting a YouTube to assuage the “show me the implementation” isn’t going to help with my cynicism.

They clearly are not connected to WiFi. You’re concocting a pretty far fetched theory at this point.

Asking for evidence isn’t a “far fetched theory.”

A video isn’t evidence.

I’m looking forward to more info proving the claims are accurate.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#35
I've seen at least a couple of papers before with similar claims, and still nothing I can run on my phone, so I'm not holding my breath yet.

It seems a bit disingenuous to compare with Stable Diffusion taking 50 steps, though; with the newer schedulers you can consistently get great images in 12 steps of diffusion, probably less if you're a bit careful with exact parameters/model fine tuning choice.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#36
post #34

Earlier quoted context omitted.

They clearly are not connected to WiFi. You’re concocting a pretty far fetched theory at this point.

Asking for evidence isn’t a “far fetched theory.” A video isn’t evidence. I’m looking forward to more info proving the claims are accurate.

Videos are absolutely evidence. You’re looking for someone to replicate their findings, which is fine, but your basis for believing it to be possibly fraudulent is far-fetched.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#37
post #21

Why focus on mobile? Near real-time rendering while entering a prompt on desktop would be even more amazing! Imagine e.g. UI sliders for adding weight to multi-prompts like "night time" (ideally sliding from [day time]:1, [night time]:0 to both zero, to all night with 0,1).

- It's significantly easier to monetize mobile apps (both with ads and in-app purchases) - Open projects already dominate the desktop space - There are a growing number of younger people who aren't really computer literate, or otherwise just use their phone as their primary computing device. - Phones go into social situations where desktops/laptops don't.

Phones also have cameras built-in, which would fit well with img2img.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#38

I've seen at least a couple of papers before with similar claims, and still nothing I can run on my phone, so I'm not holding my breath yet. It seems a bit disingenuous to compare with Stable Diffusion taking 50 steps, though; with the newer schedulers you can consistently get great images in 12 steps of diffusion, probably less if you're a bit careful with exact parameters/model fine tuning choice.

Steps isn't an apples-to-apples comparison though because some schedulers have longer steps (time-wise) than others.

Re: SnapFusion: Text-to-Image Diffusion Model on Mobile Devices Within Two Seconds

#40
I thought for fast text-to-image synthesizer you would need a GAN instead of a diffusion model. GAN models are much faster. Though apparently they aren't quite competitive with diffusion models in terms of quality. See

https://arxiv.org/abs/2301.09515

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