Fast Uncertainty Quantification for Deep Object Pose Estimation

16 November 2020

Papers citing "Fast Uncertainty Quantification for Deep Object Pose Estimation"

8 / 8 papers shown

Title
Alignist: CAD-Informed Orientation Distribution Estimation by Fusing Shape and Correspondences Shishir Reddy Vutukur R. Haugaard Junwen Huang Benjamin Busam Tolga Birdal 38 0 0 10 Sep 2024
DTF-Net: Category-Level Pose Estimation and Shape Reconstruction via Deformable Template Field Haowen Wang Zhipeng Fan Zhen Zhao Zhengping Che Zhiyuan Xu Dong Liu Feifei Feng Yakun Huang Xiuquan Qiao Jian Tang 28 7 0 04 Aug 2023
Shape Completion with Prediction of Uncertain Regions Matthias Humt Dominik Winkelbauer Ulrich Hillenbrand 19 4 0 01 Aug 2023
Object-centric Representations for Interactive Online Learning with Non-Parametric Methods Nikhil Shinde Jacob J. Johnson Sylvia L. Herbert Michael C. Yip LM&Ro OffRL 27 1 0 19 Jul 2023
Ambiguity-Aware Multi-Object Pose Optimization for Visually-Assisted Robot Manipulation Myung-Hwan Jeon Jeong-Man Kim J. Ryu Ayoung Kim 19 7 0 02 Nov 2022
Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation Rishabh Jangir Nicklas Hansen Sambaran Ghosal Mohit Jain Xiaolong Wang 24 65 0 19 Jan 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015