SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid
Shape Correspondence

SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence

16 September 2022

Souhaib Attaiki

Papers citing "SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence"

7 / 57 papers shown

Title
Universal Correspondence Network Chris Choy JunYoung Gwak Silvio Savarese Manmohan Chandraker 53 369 0 11 Jun 2016
Learning shape correspondence with anisotropic convolutional neural networks Davide Boscaini Jonathan Masci Emanuele Rodolà M. Bronstein 3DPC 156 508 0 20 May 2016
LIFT: Learned Invariant Feature Transform K. M. Yi Eduard Trulls Vincent Lepetit Pascal Fua 108 1,206 0 30 Mar 2016
3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions Andy Zeng Shuran Song Matthias Nießner Matthew Fisher Jianxiong Xiao Thomas Funkhouser 3DV 3DPC 76 987 0 27 Mar 2016
PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors Vassileios Balntas Edward Johns Lilian Tang K. Mikolajczyk 78 173 0 19 Jan 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.5K 149,842 0 22 Dec 2014
Coupled quasi-harmonic bases Artiom Kovnatsky M. Bronstein A. Bronstein K. Glashoff Ron Kimmel 104 200 0 28 Sep 2012