Frontier3DBench：跨对象、场景和交互开放世界的代码智能体 3D 创作基准测试
Frontier3DBench: Benchmarking Coding Agents for 3D Creation across Objects, Scenes, and Interactive Open Worlds
Frontier3DBench 统一评估了 145 项任务中代码智能体在对象、场景和交互式 3D 世界创建上的能力，GPT-6.1-sol 在对象和场景层表现最佳，总得分 66.02/100，但所有配置在对象和场景任务中参考重建得分均低于文本驱动生成。生成世界在局部机制上平均 83.08/100，但在运动清除和状态化工作流上仅分别为 20.82 和 30.26，显示协调活动完成仍是核心瓶颈。
Published on Nov 6
Authors:
,
,
,
,
,
,
,
,
,
,
,
Abstract
A unified 145-task benchmark evaluates coding agents across object, scene, and interactive 3D creation, revealing reference fidelity and coordinated activity completion as central bottlenecks.
Coding agents combine visual understanding with program execution, offering a new route to automated 3D creation. By translating images and instructions into editable programs, they bring reconstruction, generation, and editing into a shared workflow. Yet existing benchmarks fragment evaluation across task scopes and protocols, leaving their capabilities across construction levels unclear. We propose Frontier3DBench, a unified benchmark of 145 tasks across 9 categories spanning object, scene, and interactive open-world creation, with joint evaluation of appearance, structure, and behavior. Experiments with 11 model-harness configurations reveal strengths that vary by level: GPT-6.1-sol leads the object and scene levels and achieves the highest overall score of 66.02/100, whereas GPT-6-astra leads interactive world construction. However, all configurations score lower on reference reconstruction than on text-driven generation in object and scene tasks. Producing plausible content thus remains easier than reproducing specified geometry, layouts, and visual details. Moreover, generated worlds average 83.08/100 on local mechanisms but only 20.82 on motion clearance and 30.26 on stateful workflows: individual mechanisms often function, whereas complete activities that require coordinated actions and persistent state remain difficult. These results identify reference fidelity and coordinated activity completion as central bottlenecks for coding agents in 3D creation.
View arXiv page View PDF Project page Add to collection
Get this paper in your agent:
hf papers read 2611.09017
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash
Models citing this paper 0
No model linking this paper
Cite arxiv.org/abs/2611.09017 in a model README.md to link it from this page.
Datasets citing this paper 1
Einsia/Frontier3DBench
Viewer • Updated about 2 hours ago • 145
Spaces citing this paper 0
No Space linking this paper
Cite arxiv.org/abs/2611.09017 in a Space README.md to link it from this page.
Collections including this paper 2
来源: Hugging Face Daily Papers · huggingface.co