Point-E

Point-E

OpenAI
+
+

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About

While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view using a text-to-image diffusion model and then produces a 3D point cloud using a second diffusion model which conditions the generated image. While our method still falls short of the state-of-the-art in terms of sample quality, it is one to two orders of magnitude faster to sample from, offering a practical trade-off for some use cases. We release our pre-trained point cloud diffusion models, as well as evaluation code and models, at this https URL.

About

SpAItial is an AI platform focused on building and deploying Spatial Foundation Models (SFMs), a new class of generative AI systems designed to create and understand 3D environments with physical realism and spatial awareness. Unlike traditional models that generate pixels or text independently, SpAItial’s technology operates directly on 3D structures, capturing geometry, materials, lighting, and physics from the outset to produce coherent, interactive worlds. Its flagship model, Echo-2, can transform a single image into a fully explorable, photorealistic 3D scene using techniques like Gaussian splatting, enabling users to navigate and render environments in real time. It is built around a physically grounded understanding of space-time, allowing AI to reason about how objects exist, interact, and evolve within an environment rather than producing disconnected outputs. This approach reduces inconsistencies common in traditional generative AI and enables more accurate simulation.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone searching for a system for generating 3D point clouds from complex prompts

Audience

Developers and creators building immersive 3D, AR/VR, or robotics applications who need AI that can generate and reason about realistic spatial environments from minimal input

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

OpenAI
Founded: 2015
United States
openai.com/research/point-e

Company Information

spAItial
United States
app.spaitial.ai/

Alternatives

Alternatives

SuperSplat

SuperSplat

PlayCanvas
Shap-E

Shap-E

OpenAI
Spatial Studio

Spatial Studio

Real Horizons
RODIN

RODIN

Microsoft
Splat Labs

Splat Labs

ROCK Robotic
Seed3D

Seed3D

ByteDance
Genie 3

Genie 3

Google DeepMind

Categories

Categories

Integrations

No info available.

Integrations

No info available.
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