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Draw Step by Step: Reconstructing CAD Construction Sequences from Point Clouds via Multimodal Diffusion.

1 Jan 2024CVPR 2024 1archive 2025-07-28

Weijian Ma, Shuaiqi Chen, Yunzhong Lou, Xueyang Li, Xiangdong Zhou

Reconstructing CAD construction sequences from raw 3D geometry serves as an interface between real-world objects and digital designs. In this paper we propose CAD-Diffuser a multimodal diffusion scheme aiming at integrating top-down design paradigm into generative reconstruction. In particular we unify CAD point clouds and CAD construction sequences at the token level guiding our proposed multimodal diffusion strategy to understand and link between the geometry and the design intent concentrated in construction sequences. Leveraging the strong decoding abilities of language models the forward process is modeled as a random walk between the original token and the [MASK] token while the reverse process naturally fits the masked token modeling scheme. A volume-based noise schedule is designed to encourage outline-first generation decomposing the top-down design methodology into a machine-understandable procedure. For tokenizing CAD data of multiple modalities we introduce a tokenizer with a self-supervised face segmentation task to compress local and global geometric information for CAD point clouds and the CAD construction sequence is transformed into a primitive token string. Experimental results show that our CAD-Diffuser can perceive geometric details and the results are more likely to be reused by human designers.

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Tasks

3D geometryCAD Reconstruction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
CAD Reconstruction DeepCAD CAD-Diffuser Camfer Distance (median) 3.02 #4 of 11 Archive leaderboard report
CAD Reconstruction DeepCAD CAD-Diffuser IoU 74.3 #4 of 11 Archive leaderboard report
CAD Reconstruction Fusion 360 Gallery CAD-Diffuser Chamfer Distance (median) 3.85 #7 of 11 Archive leaderboard report
CAD Reconstruction Fusion 360 Gallery CAD-Diffuser IoU 63.2 #7 of 11 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Diffusion

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