Connectionists: Call for Competition - Layout Segmentation of Ancient Manuscripts

[Claudio Piciarelli]

(apologies for multiple copies)

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CALL FOR COMPETITION: SAM 2024
https://ai4ch.uniud.it/udiadscomp/
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We are glad to announce SAM: International Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts, in conjunction with the 18th International Conference on Document Analysis and Recognition ICDAR 2024.

Competition Overview:
Layout segmentation is a critical aspect of Document Image Analysis, particularly when it comes to ancient manuscripts. It consists in decomposing the document in several regions representing title, main text, paratext, etc.. We invite the research community to address this task on U-DIADS-Bib, a novel dataset of fully-labelled ancient manuscripts.

Competition Tasks:
We propose two separate tasks. Participants can try only one of them or both.

  *   Few-Shot Segmentation: participants are asked to develop a layout segmentation system using only three images for each manuscript as a training set
  *   Many-Shot Segmentation: participants have access to the full dataset (except for the private data that will be used for the final evaluation)

Important Dates:

  *   Beginning of Track 1: January 15, 2024
  *   Deadline of Track 1: March 3, 2024
  *   Beginning of Track 2: Match 4, 2024
  *   Deadline of Track 2: March 31, 2024

Prizes:
Winners of each task will be eligible for a cash prize of 300 EUR sponsored by CVPL - Italian Association for Computer Vision, Pattern Recognition and Machine Learning, IAPR Italian chapter.

For any additional information, please visit the website: https://ai4ch.uniud.it/udiadscomp/

Organizers:
Silvia Zottin, zottin.silvia at spes.uniud.it<mailto:zottin.silvia at spes.uniud.it>
Axel De Nardin, denardin.axel at spes.uniud.it<mailto:denardin.axel at spes.uniud.it>
Claudio Piciarelli, claudio.piciarelli at uniud.it<mailto:claudio.piciarelli at uniud.it>
Gian Luca Foresti, gianluca.foresti at uniud.it<mailto:gianluca.foresti at uniud.it>
Emanuela Colombi, emanuela.colombi at uniud.it<mailto:emanuela.colombi at uniud.it>
AI4CH - Artificial Intelligence for Cultural Heritage Lab, University of Udine. https://ai4ch.uniud.it/
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