04/
2020
I joined IMAGINE team as a research intern.
Research
I am interested in 6D object pose estimation. My current research focuses on scalable 3D object
detection and 6D pose estimation to handle arbitrary, previously-unseen objects.
GigaPose: Fast and Robust Novel Object Pose Estimation via One Correspondence
A "hybrid" template-patch correspondence approach that is fast, robust, and more accurate to
estimate 6D pose of novel objects in RGB images. GigaPose predicts 6D object pose from a
single 2D-to-2D correspondence.
Van Nguyen Nguyen,
Thibault Groueix,
Mathieu Salzmann,
Vincent LepetitCVPR, 2024
project
pagearXivgithub
@inproceedings{nguyen2024gigaPose,
title={{GigaPose: Fast and Robust Novel Object Pose Estimation via One
Correspondence}},
author={Nguyen, Van Nguyen and Groueix, Thibault and Salzmann, Mathieu and Lepetit,
Vincent},
booktitle={{Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}},
year={2024}
}
@inproceedings{nguyen2024nope,
title={{NOPE: Novel Object Pose Estimation from a Single Image}},
author={Nguyen, Van Nguyen and Groueix, Thibault and Ponimatkin, Georgy and Hu, Yinlin and Marlet, Renaud and Salzmann, Mathieu and Lepetit, Vincent},
booktitle={{Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}},
year={2024}
}
CNOS: A Strong Baseline for CAD-based Novel Object Segmentation
A method that can segment novel objects for a given RGB image from only their CAD models.
Based on Segmenting Anything, DINOv2, CNOS is a strong baseline for Task 5 and 6 in the
BOP
challenge 2023.
Van Nguyen Nguyen,
Thibault Groueix,
Georgy Ponimatkin,
Vincent Lepetit,
Tomáš HodaňICCV 2023 R6D Workshop, 2023
project
pagearXivgithub
@inproceedings{nguyen2023cnos,
title={{CNOS: A Strong Baseline for CAD-based Novel Object Segmentation}},
author={Nguyen, Van Nguyen and Groueix, Thibault and Ponimatkin, Georgy and
Lepetit,
Vincent and Hodan, Tomas},
booktitle={{Proceedings of the IEEE/CVF International Conference on Computer
Vision}},
year={2023}
}
PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6DoF Tracking
A method for tracking the 6D motion of objects in RGB video sequences when neither
training images nor even the 3D geometry of the objects is available.
Van Nguyen Nguyen+,
Yuming Du+,
Yang Xiao,
Michaël Ramamonjisoa,
Vincent Lepetit3DV Oral, 2022 (+ equal contribution)
arXivgithub
@inproceedings{nguyen3DV22,
author = {Nguyen, Van Nguyen and Du, Yuming and Xiao, Yang and Ramamonjisoa, Michael and Lepetit, Vincent},
title = {{PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6DoF
Tracking}},
booktitle = {{International Conference on 3D Vision}},
year = {2022}
}
Templates for 3D Object Pose Estimation Revisited: Generalization to New
Objects and Robustness to Occlusions
A method that can recognize objects and estimate their 3D pose in color images even
under partial occlusions. Our method requires neither a training phase on these objects
nor real images depicting them, only their CAD models.
Van Nguyen Nguyen,
Yinlin Hu,
Yang Xiao,
Mathieu Salzmann,
Vincent LepetitCVPR, 2022
project
pagearxivgithub
@inproceedings{nguyen2022template,
author = {Nguyen, Van Nguyen and Hu, Yinlin and Xiao, Yang and Salzmann, Mathieu and
Lepetit, Vincent},
title = {{Templates for 3D Object Pose Estimation Revisited: Generalization to New
Objects and Robustness to Occlusions}},
booktitle = {{Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition}},
year = {2022}
}