Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose
Estimation

Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation

20 December 2020

Nassir Navab

Leonidas J. Guibas

Papers citing "Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation"

15 / 15 papers shown

Title
Towards Robust Probabilistic Modeling on SO(3) via Rotation Laplace Distribution Yingda Yin Jiangran Lyu Yang Wang Heru Wang H. Wang B. Chen OOD 94 4 0 24 Feb 2025
Alignist: CAD-Informed Orientation Distribution Estimation by Fusing Shape and Correspondences Shishir Reddy Vutukur R. Haugaard Junwen Huang Benjamin Busam Tolga Birdal 33 0 0 10 Sep 2024
HR-APR: APR-agnostic Framework with Uncertainty Estimation and Hierarchical Refinement for Camera Relocalisation Changkun Liu Shuai Chen Yukun Zhao Huajian Huang V. Prisacariu Tristan Braud 37 9 0 22 Feb 2024
Kernel Stein Discrepancy on Lie Groups: Theory and Applications Xiaoda Qu Xiran Fan B. Vemuri 32 0 0 21 May 2023
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction David M. Klee Ondrej Biza Robert W. Platt Robin G. Walters 21 18 0 27 Feb 2023
AQuaMaM: An Autoregressive, Quaternion Manifold Model for Rapidly Estimating Complex SO(3) Distributions Michael A. Alcorn 27 0 0 21 Jan 2023
Towards Explainability in Modular Autonomous Vehicle Software Hongrui Zheng Zirui Zang Shuo Yang Rahul Mangharam 25 0 0 01 Dec 2022
Learning Implicit Probability Distribution Functions for Symmetric Orientation Estimation from RGB Images Without Pose Labels Arul Selvam Periyasamy Luis Denninger Sven Behnke 13 1 0 21 Nov 2022
Self-Aligning Depth-regularized Radiance Fields for Asynchronous RGB-D Sequences Yuxin Huang Yongliang Shi Zirui Wu Yuantao Chen Runyi Yang Z. Zhu Chao Hou Hao Zhao Guyue Zhou 3DH 28 0 0 14 Nov 2022
Local_INN: Implicit Map Representation and Localization with Invertible Neural Networks Zirui Zang Hongrui Zheng Johannes Betz Rahul Mangharam 26 6 0 24 Sep 2022
6D Camera Relocalization in Visually Ambiguous Extreme Environments Yang Zheng Tolga Birdal Fei Xia Yanchao Yang Yueqi Duan Leonidas J. Guibas 13 2 0 13 Jul 2022
Probabilistic Rotation Representation With an Efficiently Computable Bingham Loss Function and Its Application to Pose Estimation Hiroya Sato Takuya Ikeda Koichi Nishiwaki 33 1 0 09 Mar 2022
Projective Manifold Gradient Layer for Deep Rotation Regression Jiayi Chen Yingda Yin Tolga Birdal Baoquan Chen Leonidas J. Guibas He-Nan Wang 44 33 0 22 Oct 2021
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold Kieran A. Murphy Carlos Esteves Varun Jampani Srikumar Ramalingam A. Makadia 18 76 0 10 Jun 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015