CADENA：分步式CAD逆向工程

摘要

计算机辅助设计（CAD）支撑着现代工程，但将现有形状转换为可编辑模型仍需大量专家工作。大多数AI系统一次性生成整个CAD程序，从不检查中间几何体。相比之下，人类工程师逐特征构建零件，在每次操作后检查还有哪些部分需要建模。我们提出CADENA（西班牙语中意为“链”），该模型将三维网格重建为参数化CAD程序，逐步扩展其操作序列，并在每一步中将目标与当前预测的几何体进行比较。我们还解决了机械零件逆向工程方法缺乏评估基准的问题，引入了CADENA-Bench——一个衡量各类机械零件性能的基准。CADENA在CADENA-Bench以及DeepCAD、Fusion 360和MCB数据集上均优于先前方法。代码可在https://github.com/zhemdi/cadena获取，模型权重可在https://huggingface.co/kulibinai/cadena获取，CADENA-Bench可在https://huggingface.co/datasets/kulibinai/cadena-bench获取。

English

Computer-Aided Design (CAD) underpins modern engineering, yet converting existing shapes into editable models still demands substantial expert effort. Most AI systems emit the entire CAD program in a single pass, never inspecting the intermediate geometry. In contrast, human engineers build a part feature by feature, checking after each operation what remains to be modeled. We introduce CADENA (Spanish for "chain"), a model that reconstructs a 3D mesh as a parametric CAD program, growing its sequence of operations one at a time and comparing the target with the currently predicted geometry at every step. We also address the lack of benchmarks for evaluating reverse-engineering methods on mechanical parts, introducing CADENA-Bench, a benchmark that measures performance across categories of mechanical parts. CADENA outperforms prior methods on CADENA-Bench and on the DeepCAD, Fusion 360, and MCB datasets. Code is available at https://github.com/zhemdi/cadena, model weights at https://huggingface.co/kulibinai/cadena, and CADENA-Bench at https://huggingface.co/datasets/kulibinai/cadena-bench.