GET3D

GET3D

NVIDIA
Seed3D

Seed3D

ByteDance
+
+

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About

We generate a 3D SDF and a texture field via two latent codes. We utilize DMTet to extract a 3D surface mesh from the SDF and query the texture field at surface points to get colors. We train with adversarial losses defined on 2D images. In particular, we use a rasterization-based differentiable renderer to obtain RGB images and silhouettes. We utilize two 2D discriminators, each on RGB image, and silhouette, respectively, to classify whether the inputs are real or fake. The whole model is end-to-end trainable. As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train performant 3D generative models that synthesize textured meshes which can be directly consumed by 3D rendering engines, thus immediately usable in downstream applications.

About

Seed3D 1.0 is a foundation-model pipeline that takes a single input image and generates a simulation-ready 3D asset, including closed manifold geometry, UV-mapped textures, and physically-based rendering material maps, designed for immediate integration into physics engines and embodied-AI simulators. It uses a hybrid architecture combining a 3D variational autoencoder for latent geometry encoding, and a diffusion-transformer stack to generate detailed 3D shapes, followed by multi-view texture synthesis, PBR material estimation, and UV texture completion. The geometry branch produces watertight meshes with fine structural details (e.g., thin protrusions, holes, text), while the texture/material branch yields multi-view consistent albedo, metallic, and roughness maps at high resolution, enabling realistic appearance under varied lighting. Assets generated by Seed3D 1.0 require minimal cleanup or manual tuning.

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 seeking a generative model of high quality 3D textured shapes learned from images

Audience

Engineers and creators in robotics, gaming, AR/VR and simulation seeking a tool to convert 2D images into high-fidelity 3D assets ready for physics engines and virtual-world application

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

No information available.
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

NVIDIA
United States
nv-tlabs.github.io/GET3D/

Company Information

ByteDance
Founded: 2012
China
seed.bytedance.com/en/seed3d

Alternatives

Seed3D

Seed3D

ByteDance

Alternatives

Hi3D

Hi3D

Math Magic

Categories

Categories

Integrations

No info available.

Integrations

No info available.
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