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Survey on Modeling of Human-made Articulated Objects
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3D modeling of articulated objects is a research problem within computer vision, graphics, and robotics. Its objective is to understand the shape and motion of the articulated components, represent the geometry and mobility of object parts, and create realistic models that reflect articulated objects in the real world. This survey provides a comprehensive overview of the current state-of-the-art in 3D modeling of articulated objects, with a specific focus on the task of articulated part perception and articulated object creation (reconstruction and generation). We systematically review and discuss the relevant literature from two perspectives: geometry modeling (i.e., structure and shape of articulated parts) and articulation modeling (i.e., dynamics and motion of parts). Through this survey, we highlight the substantial progress made in these areas, outline the ongoing challenges, and identify gaps for future research. Our survey aims to serve as a foundational reference for researchers and practitioners in computer vision and graphics, offering insights into the complexities of articulated object modeling.
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Cited by 3 Pith papers
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Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling
Articulate AnyMesh converts arbitrary rigid 3D meshes into articulated objects by combining VLM-driven part segmentation, geometry-aware joint estimation, and optional shape completion.
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ArtFormer: Controllable Generation of Diverse 3D Articulated Objects
ArtFormer generates diverse 3D articulated objects from text or images using a transformer over tree-structured part tokens with a diffusion SDF shape prior, reporting quality and diversity gains over modified NAP and...
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Generalizable Articulated Object Perception with Superpoints
A superpoint-based model with SAM-guided query selection improves part segmentation on GAPartNet, reaching 77.9% AP50 on seen categories and 39.3% on unseen categories.
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