CC3D-Ops dataset

CC3D-Ops

The CC3D-Ops dataset contains 37k+ B-Reps with the corresponding per-face CAD operation type and step annotations. These labels were extracted using the Solidworks API. The B-Reps and their corresponding annotations constitute an extension of the CC3D dataset [1]. While the Fusion360 dataset [2] contains a similar number of B-Reps (35k+) with the corresponding CAD operation type labels, it does not provide CAD operation step labels, and it includes relatively simple CAD models. The proposed CC3D-Ops dataset comes with more complex models that are closer to real-world industrial challenges.

[1] Pvdeconv: Point-voxel deconvolution for autoencoding cad construction in 3d, Cherenkova, Kseniya, Djamila Aouada, and Gleb Gusev, 2020 IEEE International Conference on Image Processing (ICIP).

[2] Fusion 360 gallery: A dataset and envi- ronment for programmatic cad construction from human de- sign sequences, Karl D. D. Willis, Yewen Pu, Jieliang Luo, Hang Chu, Tao Du, Joseph G. Lambourne, Armando Solar-Lezama, and Wojciech Matusik, ACM Trans. Graph., 40(4), 2021.

Requesting CC3D-Ops

The CC3D-Ops dataset is available for use by external parties. Due to agreements signed by the volunteer models, a license agreement must be requested and signed by the recipient and the research administration office director of your institution before the data can be provided. To make a request for the data, please contact us on Shapify3D (at) uni (dot) lu or use the following contact form.

Note:

(1) Once a license agreement is signed, we will give access to download the data.

(2) If this data is used, in whole or in part, the following paper must be referenced:

CADOps-Net: Jointly Learning CAD Operation Types and Steps from Boundary-Representations, Elona Dupont, Kseniya Cherenkova, Anis Kacem, Sk Aziz Ali, Ilya Arzhannikov, Gleb Gusev, and Djamila Aouada, 2022 International Conference on 3D Vision (3DV).

Pvdeconv: Point-voxel deconvolution for autoencoding cad construction in 3d, Cherenkova, Kseniya, Djamila Aouada, and Gleb Gusev, 2020 IEEE International Conference on Image Processing (ICIP).