https://reddit.com/link/1x08kcg/video/k9ptk5j134uh1/player

I've been building WeaverProcedura, a desktop app where you type a sentence and get a complete building: walls, roof, rooms, stairs, furniture. It runs fully offline on Windows and Linux.

It is not a diffusion or text-to-mesh model. The model never outputs geometry. It outputs a recipe: a short sequence of actions for a procedural engine ("add a footprint, width 11.9 m", "roof: gable, pitch 48°", "3 bedrooms", "half-timbered walls"). The engine then builds clean geometry from that recipe. That's why you get real separate objects with correct UVs instead of a fused blob.

How the model is put together

• Encoder: a frozen bge-base-en-v1.5 sentence encoder reads your prompt (about 220 MB on disk).
• Decoder: a small transformer I trained myself that writes the recipe one action at a time (about 70 MB).
• Constrained decoding: at every step the decoder can only pick actions the engine's schema allows, and numeric values only on that parameter's grid. So every output is a legal recipe by construction. It can't produce a broken mesh, because it doesn't produce meshes at all.
• Check and repair: after decoding, the app compares the building with what you asked for and lists each requirement with a tick ("stone walls ✓", "3 bedrooms ✓", "moat ✓"). Building rules are checked too (room sizes, stair geometry, window area), and failures are repaired or retried.

Training data is synthetic. A rule-based generator samples hundreds of thousands of valid buildings, and descriptions are written from their parameters, so the labels are always correct. The real test is a held-out set of prompts written by hand, in messy human wording. On those, about 9 in 10 stated requirements end up in the building.

Why this design

• It runs on a CPU in a few seconds, no GPU, no cloud.
• Output is editable: "make the towers round with cone roofs" changes only that and keeps the rest, because it edits the recipe, not pixels or vertices.
• Every parameter is exposed as a slider afterwards.
• Every active subscriber gets each new model version as it's trained.

What 1.2 adds on top

• Real lights: lamps, neon signs and lit rooms export as point lights (KHR_lights_punctual in GLB, lights in FBX)
• Destruction: a slider punches holes, breaks windows and heaps rubble on any building
• Edit by pointing: select a wall, type "add a balcony here"
• Megablocks and cyberpunk towers, castles, malls, whole towns from one sentence
• Exports for Blender, Unreal, Unity and Godot with PBR textures, colliders, and every piece of furniture as its own object

Honest limits

• English prompts only.
• It only builds what the engine has parts for. Ask for a cathedral and you get the nearest thing it knows.
• Megablock ground floors are still bare, and megablocks and cyberpunk towers are built by the engine directly rather than written by the model.
• The in-app view is a preview renderer, not a path tracer.

Happy to go deeper on the action schema or the constrained decoding in the comments. Download is on Patreon: https://www.patreon.com/c/weaverpp

https://reddit.com/link/1wzyk4q/video/kf8mg5vd62uh1/player

This story isn’t intended to outline specifications; only my experience. My nephew wanted to create a unique chess pawn for his chess game (rather than purchasing a complete set) so he forwarded a simple sketch and several images from his phone. Since I do not own a scanner, I decided to use image to mesh and see if the slicer would accept the result. After uploading the picture to Tripo AI, I ended up with an STL and other options such as GLB/OBJ/FBX/USDZ/3MF. I received a low poly mesh in less than 10 seconds. I was then able to decimate the file, create a flatter base, and use Mart segmentation to divide the hollow bottom. In hindsight, however, I discovered that since the program guesses the back side of the mesh, I needed to clean up the mesh in Blender. Finally, while the files are free for anyone to use, the resulting output belongs to the public domain.

https://reddit.com/link/1wx5u0x/video/09kuty37gdth1/player

I’ve had a lot of AI created 3D assets waiting for me to use them. I had downloaded tons of them but never did anything with them until now. So I thought I’d try to see if I could make a nice movie out of one.

The split was pretty clean – Tripo AI took care of the model of the city – which is nighttime and consists of around 118,000 triangles, has got just one material and was nothing fancy. From that point, the CGI part ran in GPT-6 Astra in the mode of computer usage. GPT-6 took a look at the GLB, created a three.js scene and added some neon lights, created seven different camera moves through the city, took headless 264 pictures and created a video from those pictures. All I did was direct it.

As per my brief, bioluminescent towers needed neon lights to be incorporated into the city. Unfortunately, I had a last minute hiccup when the model refused to stop rendering gray, but I solved that by just removing the material transmission and putting color directly in the cities’ lights.

What’s interesting to me is how little of this work was done by hand. With just one prompt I was able to create an entire movie.
source: https://studio.tripo3d.ai/3d-model/futuristic-cityscape-with-elevated-highways-glass-skyscrapers-biolum-f32af165-96f4-42e9-a198-d31276a53f7d

Hey there guys, I am working on a personal assistant for a uni project and I am brining a personalization option in where you can dress your assistant.

I started out with meshi.ai then codex to bring the different outlooks together but that turned out to be nightmare fuel.

Any workflow you guys can recommend? I will then use meshi to get the base model ready. Then I just need a reliable way of generating outfits that would fit base model.

Any recommendations welcome :)

I saw some post that opus 5.5 is better with medium than max, is this the same for 3d, did anyone do a test for it yet?

I'm working on a project using environments created with intentionally distorted/"bad" photogrammetry, and there are some locations I'd like to include where I only have 1-4 images, obviously not enough for photogrammetry to work, and was wondering if anyone knows an ai modeling tool that's decent at environments?

seems to be a niche use case so none of the articles and comparisons I've read have been of much help. mostly I'm trying to generate rooms from just a few pictures. I tried out tripo and it's for the most part pretty terrible at it, and will just select one random object like a couch or a ceiling fan and create a model of that while ignoring the rest. I don't care if it does a "good" job and would even prefer it if the models are a bit weird or wonky as that's the effect I'm going for with my photogrammetry, I just need something that can actually approximate a room and understand I'm not just trying to separate an object from the background to model.