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Authors: Robin Deléarde 1 ; 2 ; Camille Kurtz 1 ; Philippe Dejean 2 and Laurent Wendling 1

Affiliations: 1 LIPADE, Université de Paris, France ; 2 Magellium, Artal Group, Toulouse, France

Keyword(s): Segmentation with Test Clues, Weakly-supervised Segmentation, Region Proposal, Knowledge Transfer.

Abstract: We propose a pipeline (SegMyO – Segment my object) to automatically extract segmented objects in images based on given labels and / or bounding boxes. When providing the expected label, our system looks for the closest label in the list of outputs, using a measure of semantic similarity. And when providing the bounding box, it looks for the output object with the best coverage, based on several geometric criteria. Associated with a semantic segmentation model trained on a similar dataset, or a good region proposal algorithm, this pipeline provides a simple solution to segment efficiently a dataset without requiring specific training, but also to the problem of weakly-supervised segmentation. This is particularly useful to segment public datasets available with weak object annotations (e.g., bounding boxes and labels from a detection, labels from a caption) coming from an algorithm or from manual annotation. An experimental study conducted on the PASCAL VOC 2012 dataset shows that the se simple criteria embedded in SegMyO allow to select the proposal with the best IoU score in most cases, and so to get the best of the pre-segmentation. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Deléarde, R.; Kurtz, C.; Dejean, P. and Wendling, L. (2021). Segment My Object: A Pipeline to Extract Segmented Objects in Images based on Labels or Bounding Boxes. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-488-6; ISSN 2184-4321, pages 618-625. DOI: 10.5220/0010324006180625

@conference{visapp21,
author={Robin Deléarde. and Camille Kurtz. and Philippe Dejean. and Laurent Wendling.},
title={Segment My Object: A Pipeline to Extract Segmented Objects in Images based on Labels or Bounding Boxes},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2021},
pages={618-625},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010324006180625},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Segment My Object: A Pipeline to Extract Segmented Objects in Images based on Labels or Bounding Boxes
SN - 978-989-758-488-6
IS - 2184-4321
AU - Deléarde, R.
AU - Kurtz, C.
AU - Dejean, P.
AU - Wendling, L.
PY - 2021
SP - 618
EP - 625
DO - 10.5220/0010324006180625