Seed3D 1.0：从图像到高保真仿真就绪的3D资产

摘要

开发具身智能体需要能够平衡内容多样性与物理准确性的可扩展训练环境。世界模拟器虽能提供此类环境，却面临双重挑战：基于视频的方法可生成多样化内容，但缺乏支持交互式学习的实时物理反馈；而基于物理的引擎虽能提供精确动力学模拟，却因昂贵的人工资产创建面临可扩展性限制。我们推出Seed3D 1.0——一个从单张图像生成可直接投入仿真的三维资产的基础模型，在保持物理严谨性的同时解决了可扩展性难题。与现有三维生成模型不同，本系统生成的资产具备精确几何结构、完美对齐的贴图以及符合物理规律的真实材质。这些资产只需简单配置即可直接集成到物理引擎中，适用于机器人操作与仿真训练场景。该系统不仅能生成独立物体，还可通过物体组装实现完整场景的规模化生成。通过实现可扩展的仿真就绪内容创建，Seed3D 1.0为推进基于物理的世界模拟器奠定了基石。该模型现已在https://console.volcengine.com/ark/region:ark+cn-beijing/experience/vision?modelId=doubao-seed3d-1-0-250928&tab=Gen3D 开放体验。

English

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

Seed3D 1.0：从图像到高保真仿真就绪的3D资产

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

摘要

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