Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry

2 May 2018

Papers citing "Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry"

6 / 6 papers shown

Title
Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker Qi Li Ziyi Shen Qian Li D. Barratt T. Dowrick Matthew J. Clarkson Tom Kamiel Magda Vercauteren Yipeng Hu 27 4 0 16 Oct 2023
Projective Manifold Gradient Layer for Deep Rotation Regression Jiayi Chen Yingda Yin Tolga Birdal Baoquan Chen Leonidas J. Guibas He-Nan Wang 47 33 0 22 Oct 2021
The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective Mathias Unberath Cong Gao Yicheng Hu Max Judish Russell H. Taylor Mehran Armand Robert Grupp 26 66 0 04 Aug 2021
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis Maxime W. Lafarge Erik J. Bekkers J. Pluim R. Duits M. Veta MedIm 27 74 0 20 Feb 2020
L6DNet: Light 6 DoF Network for Robust and Precise Object Pose Estimation with Small Datasets Mathieu Gonzalez Amine Kacete Albert Murienne É. Marchand 3DH 27 9 0 03 Feb 2020
geomstats: a Python Package for Riemannian Geometry in Machine Learning Nina Miolane Johan Mathe Claire Donnat Mikael Jorda Xavier Pennec AI4CE 37 123 0 21 May 2018