Ivan Shugurov

Orcid: 0000-0001-5413-6622

According to our database1, Ivan Shugurov authored at least 14 papers between 2019 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
Dataset
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Links

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Bibliography

2024
RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

2023
6 DoF Pose Estimation of Known and Novel Objects With Dense Correspondences.
PhD thesis, 2023

NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
WS-OPE: Weakly Supervised 6-D Object Pose Regression Using Relative Multi-Camera Pose Constraints.
IEEE Robotics Autom. Lett., 2022

PolarMesh: A Star-Convex 3D Shape Approximation for Object Pose Estimation.
IEEE Robotics Autom. Lett., 2022

DPODv2: Dense Correspondence-Based 6 DoF Pose Estimation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

NeRF-Pose: A First-Reconstruct-Then-Regress Approach for Weakly-supervised 6D Object Pose Estimation.
CoRR, 2022

WeLSA: Learning to Predict 6D Pose from Weakly Labeled Data Using Shape Alignment.
Proceedings of the Computer Vision - ECCV 2022, 2022

OSOP: A Multi-Stage One Shot Object Pose Estimation Framework.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Multi-View Object Pose Refinement With Differentiable Renderer.
IEEE Robotics Autom. Lett., 2021

2020
6 DoF Pose Estimation of Textureless Objects from Multiple RGB Frames.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

2019
DPOD: Dense 6D Pose Object Detector in RGB images.
CoRR, 2019

HomebrewedDB: RGB-D Dataset for 6D Pose Estimation of 3D Objects.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

DPOD: 6D Pose Object Detector and Refiner.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019


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