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Meet Lux3D from Manycore Tech - a new 3D generative model from Manycore Tech. Turn a single image or text prompt into a full set of editable 3D assets. No modeling skills required. But here's what makes it different: it's not just about quality. It's about cutting the cost... show more

Parul Gautam

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58,439 views • 4 days ago •via X (Twitter)

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Create a 3D model from a single image, set of images or a text prompt in < 1 minute 😮‍💨 This new AI paper called CAT3D shows us that it’ll keep getting easier to produce 3D models from 2D images — whether it’s a sparser real world 3D scan (a few photos instead of hundreds) or your favorite 2D image generator like Midjourney (just an image). How does this magic work? “This architecture is similar to video diffusion models, but with camera pose embeddings for each image instead of time embeddings. The generated views are passed into a robust 3D reconstruction pipeline to create the 3D representation (Zip-NeRF or 3DGS)”

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Bilawal Sidhu

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Meta dropped not just SAM-3 yesterday but also SAM-3D (for objects and humans)🤯 SAM 3D Body is a promptable model for recovering full-body 3D human meshes from a single image. Seems to be the new SOTA

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125,235 views • 9 months ago

the fact that i can take an image of a room and turn it into a 3d model in one shot is actually insane this took like 30 seconds from image to 3d model

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131,884 views • 9 months ago

Also the [ 🌐 Make 3d model ] feature on Photo AI has been upgraded to Tripo's new state of the art model So you can turn any AI photo or video you took into a 3d model in about a minute AI 3d models are not photorealistic yet, but as you see they're getting closer Before the face was completely distorted, now it's at least visible but still cartooney looking! 👍

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@levelsio

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Diffusion for virtual worlds: we've trained a new model to create 3D objects from text. And it's 50x faster than any alternative. We made each of these cute characters in just one minute with Genmo's new text-to-3D model. Build your own world at

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438,839 views • 2 years ago

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Meet Dreamina The way it creates videos, surprising.. You can now turn a single image or text prompt into a full cinematic AI video; no editing, no limits. This update is scary good. Here’s what I made with it 👇

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Whatever you’re building, a game, an animation, or a world of your own, 404 helps you turn ideas into usable 3D assets. Build beautiful organic worlds using 404-generated assets. Every asset in this reel was generated with 404. All you bring is the prompt. Try it out at:

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MrNeRF

52,849 views • 1 year ago

This isn’t a 3D model thrown in a box. This is pure code. No Blender, no Maya, no shortcuts. Every voxel, every jump, every movement scripted from scratch. Generative art at this level means thinking like a designer, a coder, and an artist all at once. It’s not about placing pixels. It’s about writing the rules of how a frog should exist in the Bitcoin chain. BLOCKFROGS isn’t just generative. It’s engineered. Be part of this experience Wl = 2 Freemints 5 WL to snatch Post or Quote about BLOCK | Frogs | Panthers Drop the link

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BLOCK | Frogs | Panthers

16,246 views • 1 year ago

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0 is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:

Another big drop from Hunyuan3D by Tencent. Hunyuan3D-Buffalo 1.0 is not just another text-to-3D model. The more interesting part is its approach to 3D understanding and editing. It can understand separate parts of a complete asset, extract them, remove or replace them with prompts, and edit only the selected region while keeping the rest of the geometry unchanged. That feels like a much more useful direction for 3D AI in general: not just generating a mesh once, but actually understanding its structure and letting you continue working with it. The model combines Qwen-VL, TRELLIS and Hunyuan3D, and was trained on an impressive dataset of 87 million 3D samples. Source:

Stefan 3D AI

36,034 views • 25 days ago

Experimenting with image-to-world: creating consistent 3D environments from a single photo. As someone who studied architecture, this feels like a glimpse into the future of spatial creation and I’m excited to see where World Labs takes it.

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Ian Curtis

61,754 views • 1 year ago