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 autoregressive framework for generating buildable brick structures from diverse 3D representations. BrickAnything uses point clouds as a unified geometric interface and predicts brick sequences that reconstruct the target shape under assembly constraints. To model structural dependencies among bricks, we introduce a structure-aware tree tokenization, which represents brick structures through local attachment relations. This formulation makes sequence generation more consistent with the physical construction process, and reduces invalid intermediate states. We further introduce preference-based alignment post-training, validity-constrained decoding and adaptive rollback to improve buildability objectives such as stability and geometric fidelity. Extensive experiments demonstrate that BrickAnything produces geometrically faithful and physically realizable brick structures, and that the proposed tokenization effectively reduces rollback and regeneration compared with conventional ordering strategies.

翻译：从三维形状生成物理上可搭建的积木结构不仅需要几何重建：输出还必须满足离散零件约束和结构稳定性。现有的积木生成方法要么依赖启发式优化——当目标三维形状在预定义约束下不存在可行结构时，该方法可能失效，要么生成积木序列时未显式建模底层三维几何与装配关系。本文提出BrickAnything，一种几何约束的自回归框架，可从多种三维表示生成可搭建的积木结构。BrickAnything采用点云作为统一几何接口，预测能通过装配约束重建目标形状的积木序列。为建模积木间的结构依赖性，我们引入结构感知的树状标记化方法，通过局部附着关系表征积木结构。该公式使序列生成更符合物理建造过程，并减少无效中间状态。我们进一步引入基于偏好的对齐后训练、有效性约束解码和自适应回滚机制，以优化稳定性与几何保真度等可搭建性指标。大量实验表明，BrickAnything能生成几何忠实且物理可实现的积木结构，且相较于传统排序策略，所提出的标记化方法有效减少了回滚与重生成。