首个面向专家级3D CAD编辑的基准，真实还原设计师操作流程。
neuralCAD-Edit: An Expert Benchmark for Multimodal-Instructed 3D CAD Model Editing
- 通过录制工程师实际操作视频收集真实编辑指令
- 顶尖模型（GPT 5.2）比专家低53%人类接受度
- 适合研究3D建模、多模态交互与工业级生成模型的人
我们提出neuralCAD-Edit，首个基于专业工程师真实操作的3D CAD模型编辑基准。不同于以往文本驱动的方法，本研究通过录制十位设计师在CAD软件中边操作边口述、指画的真实过程，采集了高质量的编辑请求。我们以该基准评估主流基础模型的表现，发现其在自动指标和人工评价中均与人类专家存在显著差距：即便表现最优的GPT 5.2，在人类接受度测试中仍比专家低53%（绝对值）。neuralCAD-Edit旨在为3D CAD编辑方法与基础模型的发展提供可靠评测基础。代码与数据已开源：https://autodeskailab.github.io/neuralCAD-Edit
原文摘要 · Abstract (English)
We introduce neuralCAD-Edit, the first benchmark for editing 3D CAD models collected from expert CAD engineers. Instead of text conditioning as in prior works, we collect realistic CAD editing requests by capturing videos of professional designers, interacting directly with CAD models in CAD software, while talking, pointing and drawing. We recruited ten consenting designers to contribute to this contained study. We benchmark leading foundation models against human CAD experts carrying out edits, and find a large performance gap in both automatic metrics and human evaluations. Even the best foundation model (GPT 5.2) scores 53% lower (absolute) than CAD experts in human acceptance trials, demonstrating the challenge of neuralCAD-Edit. We hope neuralCAD-Edit will provide a solid foundation against which 3D CAD editing approaches and foundation models can be developed. Code/data: https://autodeskailab.github.io/neuralCAD-Edit
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