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Generate persistent 3D worlds from a single image, bigger and better than ever! We’re excited to share our latest results and invite you to try out our world generation model in a limited beta preview.

836,380 次观看 • 1 年前 •via X (Twitter)

35 条评论

Is this a 3D model? 的头像
Is this a 3D model?1 年前

looks bad. go model your own 3D worlds instead of using this. it'll look way better

World Labs 的头像
World Labs1 年前

We’ve improved our model’s ability to generate clean, coherent geometry representing full 3D environments, and to imagine worlds in a variety of diverse styles.

World Labs 的头像
World Labs1 年前

You can explore thousands of generated worlds in our beta preview at and sign up for access to create more of your own!

World Labs 的头像
World Labs1 年前

Join the waitlist for model access directly at

Kingmakers Game 的头像
Kingmakers Game1 年前

But don't get too close to any single asset! Also don't ever try to change the lighting!

white guy 的头像
white guy1 年前

go farther than 50ft from origination point

Rosebud AI 的头像
Rosebud AI1 年前

This is huge for gaming! Some of these worlds are already available in Rosebud, can't wait to add more.

Ed Newton-Rex 的头像
Ed Newton-Rex1 年前

What's the training data?

Thunderfall 的头像
Thunderfall1 年前

This technology will be great for video games and virtual reality!

Mauro 的头像
Mauro1 年前

this works like NeRF but better. Imagine giving the AI 30 images of a house then it builds the entire 3D walkable space for you tu explore the full view

Miguel | AP 的头像
Miguel | AP1 年前

beautiful

Heather Cooper 的头像
Heather Cooper1 年前

Congratulations! It looks smooth!

hardin 的头像
hardin1 年前

Mindlessly scrolling the feed and suddenly realizing this was AI was quite the experience

Zy 的头像
Zy1 年前

Does it have to be a single image? I’d love something like this for point clouds or photogrammetry

David Xue 的头像
David Xue1 年前

Imagine training real-world workflows in simulated labs, with 100% of the reasoning data captured. That’s the future.

Anna Monaco 的头像
Anna Monaco1 年前

insane @mcneiilly

Lee Mason ᯅ 的头像
Lee Mason ᯅ1 年前

Incredible! I’ve been developing lore, architecture, environments and characters for a sprawling alien game world for years and it looks like I might be able to build it on my own over the coming years. Incredible time to be an immersive artist.

Amira Zairi 的头像
Amira Zairi1 年前

Congrats This looks awesome

FCG Studio 的头像
FCG Studio1 年前

The @theworldlabs team is always working hard!

ShinZo 的头像
ShinZo1 年前

This is nuts

Henry Williams 的头像
Henry Williams1 年前

💪💪💪

Sean McDonald 的头像
Sean McDonald1 年前

are you going to do a Quest app soon??

huw 的头像
huw1 年前

This is metaverse

Matt M 的头像
Matt M1 年前

Excited to try this out!

Dan Iel 的头像
Dan Iel1 年前

Watching this reminds me of how amazed I was running google earth for the first time. Walk down any road on the earth?! But that lasts for about 20 minutes.

steve 的头像
steve1 年前

the bg music really ties this thing together. Looks awesome

LudovicCreator 的头像
LudovicCreator1 年前

Congrats looks awesome

greeno 的头像
greeno1 年前

Why don’t you show the inage these are modeled from? These look like avg 3d environments, you must show us the image used first so we can actually see what the model is capable of. Just add the original image before each of these clips and repost.

Kirk Patrick Miller 的头像
Kirk Patrick Miller1 年前

Followed and sent you a DM. @EObadoni 👆 Just think on it. Remember what I talked of building atop our core? Yep… 😎 •

Rafsby | a KID called BEAST 的头像
Rafsby | a KID called BEAST1 年前

LET ME IN!

Louie Bacaj 的头像
Louie Bacaj1 年前

@andrewchen Is this 3D world a monolith that’s hard to change or is it video of a 3D world? Or what is it? I guess what i’m asking is, are there 3D assets that are generated that can be modified / changed / tweaked manually? say via tools like blender

mete 的头像
mete1 年前

Looks great

Tom Blake 的头像
Tom Blake1 年前

🔥🔥

Theoretically Media 的头像
Theoretically Media1 年前

Gotta dig into this! Lookin' good!

Aeris Vahn Ephelia - 𝑹𝑬𝑽 的头像
Aeris Vahn Ephelia - 𝑹𝑬𝑽1 年前

send me the invitation @theworldlabs

相关视频

One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization paper page: Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of our natural world. Many existing methods solve this problem by optimizing a neural radiance field under the guidance of 2D diffusion models but suffer from lengthy optimization time, 3D inconsistency results, and poor geometry. In this work, we propose a novel method that takes a single image of any object as input and generates a full 360-degree 3D textured mesh in a single feed-forward pass. Given a single image, we first use a view-conditioned 2D diffusion model, Zero123, to generate multi-view images for the input view, and then aim to lift them up to 3D space. Since traditional reconstruction methods struggle with inconsistent multi-view predictions, we build our 3D reconstruction module upon an SDF-based generalizable neural surface reconstruction method and propose several critical training strategies to enable the reconstruction of 360-degree meshes. Without costly optimizations, our method reconstructs 3D shapes in significantly less time than existing methods. Moreover, our method favors better geometry, generates more 3D consistent results, and adheres more closely to the input image. We evaluate our approach on both synthetic data and in-the-wild images and demonstrate its superiority in terms of both mesh quality and runtime. In addition, our approach can seamlessly support the text-to-3D task by integrating with off-the-shelf text-to-image diffusion models.

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179,061 次观看 • 3 年前