SOV-CAD: Stepwise Orthographic Views Guided CAD Modeling Sequence Reconstruction

• URL: http://arxiv.org/abs/2607.04119v1
• Date: Sun, 05 Jul 2026 05:12:58 GMT
• Title: SOV-CAD: Stepwise Orthographic Views Guided CAD Modeling Sequence Reconstruction
• Abstract summary: SOV-CAD is a framework that formulates CAD reconstruction as a sequential decision-making task.<n>It employs offline reinforcement learning with a Decision Transformer architecture.<n>It surpasses state-of-the-art methods in CAD sequence reconstruction while exhibiting strong data efficiency.
• Score: 10.5983720313455
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Reconstructing Computer-Aided Design (CAD) modeling sequences from images is crucial for preserving design intent and supporting parametric editing. However, existing methods typically generate full CAD sequences holistically, overlooking the iterative, feedback-driven nature of human design workflows. We address this limitation by introducing the rich stepwise visual supervision: at each modeling step, the system observes the target's orthographic projections, the projections of the incrementally constructed model, and the active sketch, enabling informed action selection. To effectively leverage this on-the-fly feedback, we propose SOV-CAD, a framework that formulates CAD reconstruction as a sequential decision-making task and employs offline reinforcement learning with a Decision Transformer architecture. This design incorporates continuous visual feedback guided by geometric alignment rewards, resulting in a more accurate and human-like modeling process. Extensive experiments show that SOV-CAD surpasses state-of-the-art methods in CAD sequence reconstruction while exhibiting strong data efficiency. Code of SOV-CAD is available at: https://github.com/LukePhong/SOV-CAD

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