Category Archives: AI/ML

NVIDIA’s GET3D promises text-to-model generation

Depending on how well it works, tech like this could be the greatest unlock in 3D creation the world has ever known.

The company blog post features interesting, promising details:

Though quicker than manual methods, prior 3D generative AI models were limited in the level of detail they could produce. Even recent inverse rendering methods can only generate 3D objects based on 2D images taken from various angles, requiring developers to build one 3D shape at a time.

GET3D can instead churn out some 20 shapes a second when running inference on a single NVIDIA GPU — working like a generative adversarial network for 2D images, while generating 3D objects. […]

GET3D gets its name from its ability to Generate Explicit Textured 3D meshes — meaning that the shapes it creates are in the form of a triangle mesh, like a papier-mâché model, covered with a textured material. This lets users easily import the objects into game engines, 3D modelers and film renderers — and edit them.

See also Dream Fields (mentioned previously) from Google:

Photoshop-Stable Diffusion plugin adds inpainting with masks, layer-based img2img

Christian Cantrell + the Stability devs remain a house on fire:

Here’s a more detailed (3-minute) walk-through of this free plugin:

Demo: Generating an illustrated narrative with DreamBooth

The Corridor Crew has been banging on Stable Diffusion & Google’s new DreamBooth tech (see previous) that enables training the model to understand a specific concept—e.g. one person’s face. Here they’ve trained it using a few photos of team member Sam Gorski, then inserted him into various genres:

From there they trained up models for various guys at the shop, then created an illustrated fantasy narrative. Just totally incredible, and their sheer exuberance makes the making-of pretty entertaining:

Lexica adds reverse-image search

The Stable Diffusion-centered search engine (see a few posts back) now makes it easy to turn a real-world concept into a Stable Diffusion prompt:

This seems like precisely what I pined for publicly, albeit then about DALL•E:

Honoring creators’ wishes: Source+ & “Have I Been Trained”

I’m really excited to see this work from artists Holly Dryhurst & Mat Herndon. From Input Mag:

Dryhurst and Herndon are developing a standard they’re calling Source+, which is designed as a way of allowing artists to and opt into — or out of — allowing their work being used as training data for AI. (The standard will cover not just visual artists, but musicians and writers, too.) They hope that AI generator developers will recognize and respect the wishes of artists whose work could be used to train such generative tools.

Source+ (now in beta) is a product of the organization Spawning… [It] also developed Have I Been Trained, a site that lets artists see if their work is among the 5.8 billion images in the Laion-5b dataset, which is used to train the Stable Diffusion and MidJourney AI generators. The team plans to add more training datasets to pore through in the future.

The creators also draw a distinction between the rights of living vs. dead creators:

The project isn’t aimed at stopping people putting, say, “A McDonalds restaurant in the style of Rembrandt” into DALL-E and gazing on the wonder produced. “Rembrandt is dead,” Dryhurst says, “and Rembrandt, you could argue, is so canonized that his work has surpassed the threshold of extreme consequence in generating in their image.” He’s more concerned about AI image generators impinging on the rights of living, mid-career artists who have developed a distinctive style of their own.

And lastly,

“We’re not looking to build tools for DMCA takedowns and copyright hell,” he says. “That’s not what we’re going for, and I don’t even think that would work.”

On a personal note, I’m amused to see what the system thinks constitutes “John Nack”—apparently chubby German-ish old chaps…? 🙃

Relight faces via a slick little web app

Check out ClipDrop’s relighting app, demoed here:

Fellow nerds might enjoy reading about the implementation details.

AI art -> “Bullet Hell” & Sirenhead

Shoon is a recently released side scrolling shmup,” says Vice, “that is fairly unremarkable, except for one quirk: it’s made entirely with art created by Midjourney, an AI system that generates images from text prompts written by users.’ Check out the results:

Meanwhile my friend Bilawal is putting generative imaging to work in creating viral VFX:

DALL•E outpainting arrives

Let the canvases extend in every direction! The thoughtfully designed new tiling UI makes it easy to synthesize adjacent chunks in sequence, partly overcoming current resolution limits in generative imaging:

Here’s a nice little demo from our designer Davis Brown, who takes his dad Russell’s surreal desert explorations to totally new levels:

Using DALL•E for generative fashion design

Amazing work from the always clever Karen X. Cheng, collaborating with Paul Trillo & others:

 

 
 
 
 
 
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A post shared by Karen X (@karenxcheng)

Speaking of Paul here’s a fun new little VFX creation made using DALL•E:

Photoshop previews new AI-powered photo restoration

Eng manager Barry Young writes,

The latest beta build of Photoshop contains a new feature called Photo Restoration. Whenever I have seen new updates in AI photo restoration over the last few years, I have tried the technology on an old family photo that I have of my great great great grandfather. A Scotsman who lived between 1845-1919. I applied the neural filter plus colorize technique to update the image in Photoshop. The restored photo is on the left, the original on the right. It is really astonishing how advanced AI is becoming.

Learn more about accessing the feature in Photoshop here.

Alpaca brings Stable Diffusion to Photoshop 🔥

I don’t know much about these folks, but I’m excited to see that they’re working to integrate Stable Diffusion into Photoshop:

You can add your name to the waitlist via their site. Meanwhile here’s another exploration of SD + Photoshop:

🤘Death Metal Furby!🤘

See, isn’t that a more seductive title than “Personalizing Text-to-Image Generation using Textual Inversion“? 😌 But the so-titled paper seems really important in helping generative models like DALL•E to become much more precise. The team writes:

We ask: how can we use language-guided models to turn our cat into a painting, or imagine a new product based on our favorite toy? Here we present a simple approach that allows such creative freedom.

Using only 3-5 images of a user-provided concept, like an object or a style, we learn to represent it through new “words” in the embedding space of a frozen text-to-image model. These “words” can be composed into natural language sentences, guiding personalized creation in an intuitive way.

Check out the kind of thing it yields:

“Curt Skelton,” homebrew AI influencer

[Update: Seems that much of this may be fake. :-\ Still, the fact that it’s remotely plausible is nuts!]

Good lord (and poor Conan!). This creator used:

  • DALL•E to create hundreds of similar-looking images of a face
  • Create Skeleton to convert them into a 3D model
  • DeepMotion.com to generate 3D body animation
  • Deepfake Lab to generate facial animation
  • Audio tools to deepen & distort her voice, creating a new one
@curt.skelton

♬ Mr. Roboto – Live – Styx