57 lines
2.7 KiB
Markdown
57 lines
2.7 KiB
Markdown
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title = "Stable Dreamfusion"
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description = "An exploration of 3D mesh generation through AI"
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date = 2023-06-20
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authors = ["Aron Petau"]
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banner = "/images/dreamfusion/sd_pig.png"
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[taxonomies]
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tags = [
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"3D graphics",
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"TODO, unfinished",
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"ai",
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"dreamfusion",
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"generative",
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"mesh",
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"studio d+c",
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"university of the arts berlin"
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]
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[extra]
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show_copyright = true
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show_shares = true
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+++
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## Stable Dreamfusion
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<div class="sketchfab-embed-wrapper"> <iframe title="Stable-Dreamfusion Pig" frameborder="0" allowfullscreen mozallowfullscreen="true" webkitallowfullscreen="true" allow="autoplay; fullscreen; xr-spatial-tracking" xr-spatial-tracking execution-while-out-of-viewport execution-while-not-rendered web-share width="800" height="600" src="https://sketchfab.com/models/0af6d95988e44c73a693c45e1db44cad/embed?ui_theme=dark&dnt=1"> </iframe> </div>
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## Sources
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I forked a really popular implementation that reverse engineered the Google Dreamfusion algorithm. This algorithm is closed-source and not publicly available.
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The implementation I forked is [here](https://github.com/arontaupe/stable-dreamfusion)
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This one is running on stable-diffusion as a bas process, which means we are are expected to have worse results than google.
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The original implementation is [here](https://dreamfusion3d.github.io)
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{{ youtube(id="shW_Jh728yg") }}
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## Gradio
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The reason i forked the code is so that i could implement my own gradio interface for the algorithm. Gradio is a great tool for quickly building interfaces for machine learning models. No code involves, any user can state their wish, and the mechanism will spit out a ready-to-be-rigged model (obj file)
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## Mixamo
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I used Mixamo to rig the model. It is a great tool for rigging and animating models. But before everything, it is simple. as long as you have a model with a decent humanoid shape in something of a t-pose, you can rig it in seconds. Thats exactly what i did here.
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## Unity
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I used Unity to render the model to the magic leap 1.
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Through this, i could create an interactive and immersive environment with the generated models.
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The dream was, to build a AI- Chamber of wishes.
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You pick up the glasses, state your desires and then the algorithm will present to you an almost-real object in AR.
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Due to not having access to the proprietary sources from google and the beefy, but still not quite machine-learning ready computers we have at the studio, the results are not quite as good as i hoped.
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But still, the results are quite interesting and i am happy with the outcome.
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A single generated object in the Box takes roughly 20 minutes to generate.
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Even then, the algorithm is quite particular and oftentimes will not generate anything coherent at all.
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