Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Generative AI is cool and all, but procedural 3D modeling just hits different. Check out this Houdini setup by Pepe Buendia. Why this is cool: Instead of manually placing every building and car, this system generates an NYC-style city that builds itself -- automatically spawning buildings with unique variations,...

527,289 Aufrufe • vor 1 Jahr •via X (Twitter)

10 Kommentare

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

If you liked this post, you might enjoy my writing on all things spatial intelligence and creative tech:

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

Since y’all are asking, here are my thoughts on a best of both worlds approach — the creativity and speed of generative ai w/ with fine grain control of a 3d scene graph

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

And here’s how you can do most of this in blender with geometry nodes

Profilbild von Michael Frank
Michael Frankvor 1 Jahr

We should really be using machine learning as optimization steps where it makes sense to. Renderman's AI denoiser is a good example. Trying to build "world models" from whole cloth is just using the wrong tool for the job.

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

Agreed — why not use explicit 3d approaches as a foundation?

Profilbild von Manosai
Manosaivor 1 Jahr

So cool. I don’t understand the finer details of procedural 3D modeling (still learning) but is the future with multimodal LLMs also that the rules and custom algorithms will be automatically generated? Where do you see this evolving? How much control needs to be explicitly defined by humans at the beginning?

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

yeah my hope is the LLMs read/write/edit a 3d scene graph with entity level control - so kinda like replit agent writing web apps for you - except with these trad 3d tools and engines. or you know the whole sora approach will pop out a world model and my preference is overkill :)

Profilbild von 3DGO
3DGOvor 1 Jahr

Even with this level of control this would largely be background midground work, most hero shots would have alot of manual work on top. For high end work, artists need control more than speed or ease of use.

Profilbild von Bilawal Sidhu
Bilawal Sidhuvor 1 Jahr

No doubt — but Hollywood has inordinately high standards

Profilbild von Sean Treleaven
Sean Treleavenvor 1 Jahr

You're coming around to the procedural side. Yay!

Ähnliche Videos

Alibaba presents MIMO Controllable Character Video Synthesis with Spatial Decomposed Modeling Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case training, which severely limits their applicability of modeling arbitrary characters in a short time. Recent 2D methods break this limitation via pre-trained diffusion models, but they struggle for pose generality and scene interaction. To this end, we propose MIMO, a novel framework which can not only synthesize character videos with controllable attributes (i.e., character, motion and scene) provided by simple user inputs, but also simultaneously achieve advanced scalability to arbitrary characters, generality to novel 3D motions, and applicability to interactive real-world scenes in a unified framework. The core idea is to encode the 2D video to compact spatial codes, considering the inherent 3D nature of video occurrence. Concretely, we lift the 2D frame pixels into 3D using monocular depth estimators, and decompose the video clip to three spatial components (i.e., main human, underlying scene, and floating occlusion) in hierarchical layers based on the 3D depth. These components are further encoded to canonical identity code, structured motion code and full scene code, which are utilized as control signals of synthesis process. The design of spatial decomposed modeling enables flexible user control, complex motion expression, as well as 3D-aware synthesis for scene interactions. Experimental results demonstrate effectiveness and robustness of the proposed method.

AK

148,998 Aufrufe • vor 1 Jahr

🚀 Announcing Echo — our new frontier model for 3D world generation. Echo turns a simple text prompt or image into a fully explorable, 3D-consistent world. Instead of disconnected views, the result is a single, coherent spatial representation you can move through freely. This is part of a bigger shift in AI: from generating pixels and tokens to generating spaces. Echo predicts a geometry-grounded 3D scene at metric scale, meaning every novel view, depth map, and interaction comes from the same underlying world — not independent hallucinations. Once generated, the world is interactive in real time. You control the camera, explore from any angle, and render instantly — even on low-end hardware, directly in the browser. High-quality 3D world exploration is no longer gated by expensive equipment. Under the hood, Echo infers a physically grounded 3D representation and converts it into a renderable format. For our web demo, we use 3D Gaussian Splatting (3DGS) for fast, GPU-friendly rendering — but the representation itself is flexible and can be easily adapted. Why this matters: consistent 3D worlds unlock real workflows — digital twins, 3D design, game environments, robotics simulation, and more. From a single photo or a line of text, Echo builds worlds that are reliable, editable, and spatially faithful. Echo also enables scene editing and restyling. Change materials, remove or add objects, explore design variations — all while preserving global 3D consistency. Editing no longer breaks the world. This is only the beginning. Echo is the foundation for future world models with dynamics, physical reasoning, and richer interaction — environments that don’t just look right, but behave right. Explore the generated worlds on our website and sign up for the closed beta. The era of spatial intelligence starts here. 🌍 #Echo #WorldModels #SpatialAI #3DFoundationModels Check it out:

SpAItial AI

175,909 Aufrufe • vor 6 Monaten

For generative AI to become an interesting art tool, we need much more control over the output. The slot-machine-like nature of pure text-to-image leaves too much to chance. Using the "Real-time Latent Consistency Model" that I'm using in the example here, is the first time I truly got a glimpse of a future where we'll be able to use our artistic skills and sensibility, to get control over AI image gen. Systems like these will never be able to match the quality or originality of a skilled artist, it won't surprise us in the same way an artist can. Things are a mess in terms of the training data these models are based on, and the questions about copyright concerns and about a time when everything will look the same are very valid. At some point capabilities like these will be embedded in photoshop, and anyone will be able to generate a pretty picture. But to create interesting designs, to tell original stories and to surprise us, we need creatives and artists with something on their mind. We'll be able to create immersive worlds, by making brush-strokes and sculpt marks, without needing to worry about all the dials, plugins, wires of our 3d and 2d tools today. I love to sculpt, I love to draw, and I love to explore new mediums and new ways to create. The Gen AI tools we have today are far from perfect, and things need to be steered in a better direction. For that we need artists to help point the way. Gen AI isn't going away.. it's too powerful and has the potential to allow us to tell stories like never before. Like all other big technological shifts, tech like this will come at a cost, but it will also open up new opportunities and empower a new generation of storytellers. I might be naive, but I believe that human ingenuity and creativity will persevere in this new world ♥️ #art #ai

Martin Nebelong

1,660,017 Aufrufe • vor 2 Jahren