Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations

21 July 2020

Papers citing "Procrustean Regression Networks: Learning 3D Structure of Non-Rigid Objects from 2D Annotations"

6 / 6 papers shown

Title
Non-rigid Structure-from-Motion: Temporally-smooth Procrustean Alignment and Spatially-variant Deformation Modeling Jiawei Shi Huizhong Deng Yuchao Dai 63 0 0 07 May 2024
Piecewise Planar Hulls for Semi-Supervised Learning of 3D Shape and Pose from 2D Images Y. Can Alexander Liniger D. Paudel Luc Van Gool 3DH 3DPC 70 0 0 14 Nov 2022
State of the Art in Dense Monocular Non-Rigid 3D Reconstruction Edith Tretschk Navami Kairanda R. MallikarjunB. Rishabh Dabral Adam Kortylewski Bernhard Egger Marc Habermann Pascal Fua Christian Theobalt Vladislav Golyanik 3DH 120 36 0 27 Oct 2022
MHR-Net: Multiple-Hypothesis Reconstruction of Non-Rigid Shapes from 2D Views H. Zeng Xin Yu Jiaxu Miao Yezhou Yang 3DV 91 8 0 19 Jul 2022
End-to-End Learning of Multi-category 3D Pose and Shape Estimation Y. Can Alexander Liniger D. Paudel Luc Van Gool 3DV 3DH 84 1 0 19 Dec 2021
PAUL: Procrustean Autoencoder for Unsupervised Lifting Chaoyang Wang Simon Lucey 117 8 0 31 Mar 2021