Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors
for Efficient and Robust 4D Reconstruction

Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstruction

30 March 2021

Dan Xu

Lei Zhang

Papers citing "Learning Parallel Dense Correspondence from Spatio-Temporal Descriptors for Efficient and Robust 4D Reconstruction"

6 / 6 papers shown

Title
Fluid Dynamics Network: Topology-Agnostic 4D Reconstruction via Fluid Dynamics Priors Daniele Baieri Stefano Esposito Filippo Maggioli Emanuele Rodolà AI4CE 15 3 0 17 Mar 2023
CaDeX: Learning Canonical Deformation Coordinate Space for Dynamic Surface Representation via Neural Homeomorphism Jiahui Lei Kostas Daniilidis 18 53 0 30 Mar 2022
Sign-Agnostic Implicit Learning of Surface Self-Similarities for Shape Modeling and Reconstruction from Raw Point Clouds Wenbin Zhao Jiabao Lei Yuxin Wen Jianguo Zhang K. Jia 3DPC 46 32 0 14 Dec 2020
Convolutional Occupancy Networks Songyou Peng Michael Niemeyer L. Mescheder Marc Pollefeys Andreas Geiger 3DV AI4CE 209 860 0 10 Mar 2020
Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks J. Pan Xiaoguang Han Weikai Chen Jiapeng Tang K. Jia 96 187 0 01 Sep 2019
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 210 13,886 0 02 Dec 2016