Sketch2Arti: Sketch-based Articulation Modeling of CAD Objects
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Abstract (arXiv)
Articulation modeling aims to infer movable parts and their motion parameters for a 3D object, enabling interactive animation, simulation, and shape editing. In this paper, we present Sketch2Arti, the first sketch-based articulation modeling system for CAD objects. Our key observation is that designers naturally communicate articulation intent through lightweight sketches (e.g., arrows and strokes) that indicate how parts should move, yet translating such sketches into articulated 3D models remains largely manual. Sketch2Arti bridges this gap by enabling users to specify articulation through simple 2D sketches drawn from a chosen viewpoint. Given a CAD model and user sketches, our approach automatically discovers the corresponding movable parts and predicts their motion parameters, allowing iterative modeling of multiple articulations on complex objects with fine-grained control. Importantly, Sketch2Arti is trained in a category-agnostic manner without requiring object category information, leading to strong generalization to diverse objects beyond existing articulation datasets. Moreover, for shell models lacking interior structures, Sketch2Arti supports controllable internal completion guided by user sketches, generating plausible internal components consistent with the existing geometry and predicted motion constraints. Comprehensive experiments and user evaluations demonstrate the effectiveness, controllability, and generalization of Sketch2Arti. The code, dataset, and the prototype system are at https://arlo-yang.github.io/Sketch2Arti.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 54 references that are in the map. First posted on arXiv 28 Apr 2026.
Builds on
22 of 54 references.
References · 22
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10 more
- 2024Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Modelcited by 96
- 2024SINGAPO: Single Image Controlled Generation of Articulated Parts in Objectscited by 69
- 2022Self-supervised Neural Articulated Shape and Appearance Modelscited by 51
- 2024REACTO: Reconstructing Articulated Objects from a Single Videocited by 45
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- 2025LARM: A Large Articulated-Object Reconstruction Modelcited by 12
- 2026Deep Sketch-Based 3D Modeling: A Surveycited by 3
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