Badki Abhishek, Gallo Orazio, Kautz Jan, Sen Pradeep.Hanocka Rana, Metzer Gal, Giryes Raja, Cohen-Or Daniel, Point2mesh: A self-prior for deformable meshes, 2020, arXiv preprint arXiv:2005.11084.Qi Charles Ruizhongtai, Yi Li, Su Hao, Guibas Leonidas J, Pointnet++: Deep hierarchical feature learning on point sets in a metric space, Adv Neural Inf Process Syst 30 ( 2017).Qi Charles R., Su Hao, Mo Kaichun, Guibas Leonidas J., Pointnet: Deep learning on point sets for 3d classification and segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp.In: Proceedings of the IEEE conference on computer vision and pattern recognition. A point set generation network for 3d object reconstruction from a single image. Fan Haoqiang, Su Hao, Guibas Leonidas J.Berger Matthew, Tagliasacchi Andrea, Seversky Lee M, Alliez Pierre, Guennebaud Gael, Levine Joshua A, Sharf Andrei, Silva Claudio T, A survey of surface reconstruction from point clouds, in: Computer graphics forum, Vol.Moreover, we can gain spline representations from learned shapes for CAM as the application of our method.

Comparing our method with other SOTA methods in the ABC dataset, our method is significantly superior to the existing nonlearning and learning 3D reconstruction methods in terms of surface approximation quality and sharp feature preservation. A two-stage training process is proposed, and loss functions are designed for each stage to ensure that the sharp features of the input points are learned while the surface details are fitted. Afterward, we propose an MLP-based network to train an implicit representation from input points with its extracted edge points. This detection network is light weighted and runs fast. The edge detection network uses a U-Net structure for feature encoding, and the attention module is introduced to improve the accuracy in the CAD models. Our method first extracts edge points from input points by an edge detection network and then recovers implicit surfaces while preserving the sharp features of ground-truth models. We present a novel implicit neural representation to reconstruct CAD models from point clouds with high quality.

Shapr 3d cad modeling