BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenization
arXiv:2605.26182v1 Announce Type: new Abstract: Generating physically buildable brick structures from 3D shapes requires more than geometric reconstruction: the output must also satisfy discrete part constraints and structural stability. Existing brick generation methods either rely on heuristic optimization, which can break down when the target 3D shape does not admit a feasible structure under predefined constraints, or generate brick sequences without explicitly modeling the underlying 3D geometry and assembly relations. In this work, we present BrickAnything, a geometry-conditioned autoreg
The proliferation of advanced AI techniques and improved computational graphics allows for the development of sophisticated generative models for physical structures, overcoming previous heuristic limitations.
This development pushes the boundaries of AI's ability to generate physically constrained and stable 3D designs, moving beyond mere aesthetic reconstruction to functional engineering.
The ability to generate buildable brick structures directly from 3D shapes, accounting for physical constraints, streamlines design processes for complex modular assemblies and potentially revolutionizes manufacturing pre-visualization.
- · Construction and Architecture (modular design)
- · Toy and Game Development (physical object generation)
- · Robotics (assembly planning)
- · AI/ML Research (generative models for physical constraints)
- · Traditional manual 3D design for modular structures
- · Heuristic-based brick generation software
More efficient and accurate design of modular physical structures through AI.
Accelerated development of complex robotic assembly lines that can leverage AI-generated buildable designs.
The democratization of advanced physical design and engineering capabilities, enabling non-experts to create complex, buildable objects.
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Read at arXiv cs.AI