DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction

16 October 2021

Papers citing "DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction"

9 / 9 papers shown

Title
SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformity Chengzhi Wu Yuxin Wan Hao Fu Julius Pfrommer Zeyun Zhong Junwei Zheng Jiaming Zhang Jürgen Beyerer 3DPC 45 0 0 28 Apr 2025
Denoising Functional Maps: Diffusion Models for Shape Correspondence Aleksei Zhuravlev Zorah Lähner Vladislav Golyanik DiffM 63 1 0 03 Mar 2025
Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes Krithika S. Iyer Mokshagna Sai Teja Karanam Shireen Elhabian 59 0 0 11 Feb 2025
Non-Rigid Shape Registration via Deep Functional Maps Prior Puhua Jiang Mingze Sun Ruqi Huang 19 10 0 08 Nov 2023
Deep Confidence Guided Distance for 3D Partial Shape Registration Dvir Ginzburg D. Raviv 3DV 3DPC 6 3 0 27 Jan 2022
CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds Yiming Zeng Y. Qian Zhiyu Zhu Junhui Hou Hui Yuan Ying He 3DPC 97 65 0 31 Dec 2020
FLOT: Scene Flow on Point Clouds Guided by Optimal Transport Gilles Puy Alexandre Boulch Renaud Marlet 3DPC OT 107 161 0 22 Jul 2020
3D-CODED : 3D Correspondences by Deep Deformation Thibault Groueix Matthew Fisher Vladimir G. Kim Bryan C. Russell Mathieu Aubry 3DPC 3DV 115 325 0 13 Jun 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 231 1,801 0 25 Nov 2016