Frank Michel

Affiliations:
  • Toyota Research Institute
  • Dresden University of Technology, Germany (PhD 2018)


According to our database1, Frank Michel authored at least 13 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

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Bibliography

2023
Demonstrating Mobile Manipulation in the Wild: A Metrics-Driven Approach.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

2020
BOP Challenge 2020 on 6D Object Localization.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2018
Hypothesis generation for object pose estimation - from local sampling to global reasoning.
PhD thesis, 2018


A Summary of the 4th International Workshop on Recovering 6D Object Pose.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017
Global Hypothesis Generation for 6D Object Pose Estimation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

PoseAgent: Budget-Constrained 6D Object Pose Estimation via Reinforcement Learning.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

DSAC - Differentiable RANSAC for Camera Localization.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression.
Proceedings of the British Machine Vision Conference 2015, 2015

2014
Learning 6D Object Pose Estimation Using 3D Object Coordinates.
Proceedings of the Computer Vision - ECCV 2014, 2014

6-DOF Model Based Tracking via Object Coordinate Regression.
Proceedings of the Computer Vision - ACCV 2014, 2014


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