ByteDance Seed3D Foundation Model

Seed3D 1.0 — Image to 3D Assets

A foundation model by ByteDance Seed that unites the scalability of generative modeling with the reliability of explicit physics simulation to produce diverse, high-quality 3D assets ready for physics simulation.

What is Seed3D 1.0

Seed3D 1.0 addresses three key challenges in 3D generation: high-fidelity asset generation, physics engine compatibility, and scalable scene composition. These capabilities take an important step toward enabling the world simulators that embodied AI requires.

Seed3D 1.0 Overview

Key Capabilities

🎨

High-Fidelity Geometry & Texture

Consistently outperforms baseline methods in geometry generation with higher ULIP-I and Uni3D-I scores. Strong capabilities in multi-view image and PBR materials generation, preserving fine surface details.

⚙️

Simulation-Ready Assets

Produces watertight, manifold geometry that integrates directly into Isaac Sim. VLM estimates real-world scale, and default material properties enable immediate physics simulation without manual tuning.

🏙️

Scalable Scene Generation

Extends from object to scene generation through a factorized approach. VLM extracts object instances and spatial relationships, enabling scenes from indoor offices to large-scale urban environments.

Performance Evaluation

Human Evaluation

Assessed across 43 input images along 6 key dimensions. Achieves highly competitive performance in all dimensions with strong fidelity in generating fine details and accurately reconstructing intricate features.

Human Evaluation

Geometry Generation

Consistently outperforms all baseline methods, achieving higher ULIP-I and Uni3D-I scores, indicating better alignment between generated geometry and input images.

Geometry Generation

Texture Generation

Strong capabilities in multi-view image and PBR materials generation. Reports results using ground-truth multi-view images to demonstrate PBR estimation ability.

Texture Generation

Simulation-Ready Generation

Assets integrate directly into Isaac Sim for physics-based simulation and robotic manipulation testing. The physics engine provides real-time feedback on contact forces, object dynamics, and manipulation outcomes.

Scalable generation of training data through diverse manipulation scenarios
Interactive learning via physics feedback on action consequences
Diverse multi-view, multi-modal observation data for comprehensive evaluation benchmarks

Scene Generation

Extends from object generation to scene generation through a factorized approach. A VLM extracts object instances and spatial relationships, then Seed3D synthesizes geometry and materials for each object. The final scene is assembled according to the predicted spatial layout — from indoor offices to large-scale urban scenes.

Use Cases

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Embodied AI Training

Generate scalable training data for vision-language-action models through diverse manipulation scenarios.

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Game & Content Creation

Rapidly generate high-quality 3D props and scenes for virtual environments and game development.

🏗️

Robotics Simulation

Create realistic environments for testing robotic grasping, navigation, and multi-object interaction.

Frequently Asked Questions

What is Seed3D and who made it?

Seed3D is a foundation model for 3D asset generation developed by ByteDance Seed. It creates high-fidelity 3D geometry and textures from images or text prompts, and can compose multiple objects into coherent scenes with correct spatial relationships.

What makes Seed3D different from other 3D generators?

Seed3D uses a factorized approach: it separates geometry generation from texture synthesis, which produces sharper meshes with cleaner UVs. It also integrates a VLM (vision-language model) for scene understanding, so it can place multiple generated objects in a spatially correct layout rather than just producing isolated assets.

Can I use Seed3D outputs in my game or simulation?

Seed3D is designed to be simulation-ready — outputs are compatible with physics engines and game pipelines. The geometry is clean enough for real-time rendering, and the textures are PBR-compatible. However, you should check ByteDance Seed's licensing terms for commercial use before shipping in a product.

How does Seed3D handle scene-level generation?

A vision-language model first extracts object instances and their spatial relationships from a reference image or text description. Seed3D then generates geometry and materials for each object individually, and the final scene is assembled by placing each object according to the predicted spatial layout. This works for indoor scenes like offices as well as large-scale outdoor urban environments.

Is Seed3D available on ZNIX.ai?

This page showcases Seed3D capabilities and benchmarks. ZNIX.ai focuses on AI video generation with 9 hosted models. For direct access to Seed3D, visit the official ByteDance Seed portal linked in the CTA below.

Seed3D 1.0 Frequently Asked Questions

What is Seed3D 1.0?+

Seed3D 1.0 is a foundation model developed by ByteDance Seed that generates high-quality 3D assets from a single input image. It unites generative modeling scalability with explicit physics simulation reliability, producing assets that are ready for immediate use in physics engines like Isaac Sim.

How does Seed3D generate 3D assets from a single image?+

Seed3D uses a generative model to predict 3D geometry, PBR materials, and real-world scale from a single 2D input image. The model produces watertight, manifold geometry with fine surface details preserved, enabling direct integration into simulation environments without manual cleanup.

What does simulation-ready mean?+

Simulation-ready means the generated 3D assets have watertight, manifold geometry that can be directly imported into physics engines such as NVIDIA Isaac Sim. The assets include correct real-world scale estimation, default material properties for physics interaction, and collision meshes — enabling immediate physics simulation without manual tuning or preprocessing.

How does Seed3D handle scene-level generation?+

For scene generation, Seed3D uses a factorized approach: a Vision-Language Model (VLM) first extracts object instances and their spatial relationships from the input, then Seed3D synthesizes geometry and materials for each individual object. The final scene is assembled according to the predicted spatial layout, enabling generation from indoor offices to large-scale urban environments.

Can Seed3D assets be used in game engines?+

Yes. Seed3D produces high-fidelity geometry with PBR materials that are compatible with standard game engine pipelines. The watertight manifold geometry can be imported into Unity, Unreal, and other engines. The assets are particularly suited for scenarios requiring physics interaction, such as robotics simulation and embodied AI training environments.

What is the relationship between Seed3D and embodied AI?+

Seed3D directly addresses the world simulator requirements of embodied AI. By generating diverse, physics-compatible 3D assets and scalable scenes, it provides the training data and simulation environments that vision-language-action models need for manipulation, navigation, and multi-object interaction tasks. This closes the gap between generative 3D and real-world physics readiness.

Explore Seed3D 1.0

Learn more about the Seed3D foundation model and try the official demo.