ParaPose: Parameter and Domain Randomization Optimization for Pose
Estimation using Synthetic Data

v1v2 (latest)

ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Data

IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022

2 March 2022

Frederik Hagelskjær

ArXiv (abs)PDF HTML

Papers citing "ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Data"

6 / 6 papers shown

Title
Towards an Efficient Synthetic Image Data Pipeline for Training Vision-Based Robot Systems Peter Gavriel Adam Norton Kenneth Kimble Megan Zimmerman 225 1 0 09 Nov 2024
Good Grasps Only: A data engine for self-supervised fine-tuning of pose estimation using grasp poses for verificationIEEE/SICE International Symposium on System Integration (SII), 2024 Frederik Hagelskjær 169 2 0 17 Sep 2024
Off-the-shelf bin picking workcell with visual pose estimation: A case study on the world robot summit 2018 kitting task Gregory Scafarto Madalina Ciortan Dirk Kraft 159 4 0 28 Sep 2023
Facilitating Sim-to-real by Intrinsic Stochasticity of Real-Time Simulation in Reinforcement Learning for Robot ManipulationIEEE Transactions on Artificial Intelligence (IEEE TAI), 2023 Ram Dershan Amir M. Soufi Enayati Zengjie Zhang D. Richert Homayoun Najjaran 198 3 0 12 Apr 2023
KeyMatchNet: Zero-Shot Pose Estimation in 3D Point Clouds by Generalized Keypoint Matching Frederik Hagelskjaer R. Haugaard 3DPC 3DV 212 8 0 28 Mar 2023
In-Hand Pose Estimation and Pin Inspection for Insertion of Through-Hole Components Frederik Hagelskjær D. Kraft 162 4 0 02 Aug 2022