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Authors: Mathijs Lens ; Aaron Van Campenhout and Toon Goedemé

Affiliation: EAVISE-PSI, KU Leuven Campus De Nayer, Sint-Katelijne-Waver, Belgium

Keyword(s): Pose Estimation, 6D Pose Estimation, Pacel Detection, ControlNet, Stable Diffusion.

Abstract: In this paper, we propose a method to generate synthetic training images for a more complex computer vision task compared to image classification, specifically 6D object pose detection. We demonstrate that conditioned diffusion models can generate unlimited training images for training an object pose detection model for a custom object type. Moreover, we investigate the potential of (automatically) filtering out ill-produced images in the dataset, which increases the quality of the image dataset, and show the importance of finetuning the trained model with a limited amount of real-world images to bridge the remaining sim2real domain gap. We demonstrate our pipeline in the use case of parcel box detection for the automation of delivery vans. All code is publicly available on our GitLab https://gitlab.com/EAVISE/avc/generative-ai-synthetic-training-pose-detection.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Lens, M., Van Campenhout, A. and Goedemé, T. (2025). Conditioned Generative AI for Synthetic Training of 6D Object Pose Detection. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3; ISSN 2184-4321, SciTePress, pages 324-331. DOI: 10.5220/0013130600003912

@conference{visapp25,
author={Mathijs Lens and Aaron {Van Campenhout} and Toon Goedemé},
title={Conditioned Generative AI for Synthetic Training of 6D Object Pose Detection},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={324-331},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013130600003912},
isbn={978-989-758-728-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Conditioned Generative AI for Synthetic Training of 6D Object Pose Detection
SN - 978-989-758-728-3
IS - 2184-4321
AU - Lens, M.
AU - Van Campenhout, A.
AU - Goedemé, T.
PY - 2025
SP - 324
EP - 331
DO - 10.5220/0013130600003912
PB - SciTePress

- Science and Technology Publications, Lda.
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