CubePart：開放詞彙式部件可控3D生成器

摘要

遊戲與模擬中使用的互動式 3D 資源通常會拆解為特定語意零件，以支援動畫、物理與腳本行為，然而多數生成式 3D 模型所產出的要不是一體成型的網格，就是無法對應應用特定需求的任意零件分解。我們提出 CubePart，這是一個開放詞彙、零件可控的 3D 網格生成框架，能將零件結構作為明確的推論時控制訊號。在給定全域文字提示與以開放式零件名稱列表表達的使用者定義零件架構後，我們的方法會為每個架構元素生成一組網格，這些網格在尊重指定語意結構的同時，組裝成一個連貫的物體。為實現此能力，我們引入一個可擴展的資料管線，用以建構大型開放詞彙且附有零件標籤的 3D 資料集，並搭配兩階段生成架構，將全域形狀合成與零件層級解碼分離。我們證明，所生成的資源可直接整合至遊戲引擎，並由動畫與行為腳本驅動，無需手動後處理。專案頁面：https://cubepart.github.io/

English

Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted behaviors, yet most generative 3D models produce either monolithic meshes or arbitrary part decompositions that cannot be aligned with application-specific requirements. We present CubePart, a generative framework for open-vocabulary, part-controllable 3D mesh generation that exposes part structure as an explicit inference-time control signal. Given a global text prompt and a user-defined parts schema expressed as an open-ended list of part names, our method generates a set of meshes - one per schema element - that assemble into a coherent object while respecting the specified semantic structure. To enable this capability, we introduce a scalable data pipeline to construct a large open-vocabulary, part-labeled 3D dataset, along with a two-stage generative architecture that separates global shape synthesis from part-level decoding. We demonstrate that the resulting assets can be directly integrated into game engines and driven by animation and behavior scripts without manual post-processing. Project Page: https://cubepart.github.io/