Seed3D 1.0: From Images to High-Fidelity Simulation-Ready 3D Assets

TL;DR

Seed3D 1.0 is a novel foundation model that converts single images into high-fidelity, simulation-ready 3D assets with accurate geometry and textures, facilitating scalable physics-based environment creation for embodied AI.

Contribution

The paper introduces Seed3D 1.0, a system that generates detailed, physics-compatible 3D assets from images, addressing scalability and realism in simulation environment development.

Findings

Produces assets with accurate geometry and textures

Enables direct integration into physics engines

Scales to complete scene generation

Abstract

Developing embodied AI agents requires scalable training environments that balance content diversity with physics accuracy. World simulators provide such environments but face distinct limitations: video-based methods generate diverse content but lack real-time physics feedback for interactive learning, while physics-based engines provide accurate dynamics but face scalability limitations from costly manual asset creation. We present Seed3D 1.0, a foundation model that generates simulation-ready 3D assets from single images, addressing the scalability challenge while maintaining physics rigor. Unlike existing 3D generation models, our system produces assets with accurate geometry, well-aligned textures, and realistic physically-based materials. These assets can be directly integrated into physics engines with minimal configuration, enabling deployment in robotic manipulation and simulation training. Beyond individual objects, the system scales to complete scene generation through assembling objects into coherent environments. By enabling scalable simulation-ready content creation, Seed3D 1.0 provides a foundation for advancing physics-based world simulators. Seed3D 1.0 is now available on https://console.volcengine.com/ark/region:ark+cn-beijing/experience/vision?modelId=doubao-seed3d-1-0-250928&tab=Gen3D