Program is in public. (updated at July 2nd)
Comics is a medium constituted of images combining text and graphics elements. This different visual information is used by the authors to narrate a story. Nowadays, comic books are a widespread cultural expression all over the world and especially in the United States, European countries, and Asian countries. So, the terms of Comics include several categories such as Mangas, American Comics, and Franco-Belgian “Bandes Dessinées”. Each category has its own graphic style. From the research point of view, comics images are attractive targets because the structure of a comics page includes various elements (such as panels, speech balloons, captions, leading characters, text, onomatopoeia, and so on). The design of these elements strongly depends on the creativity of the author and his graphic universe. Consequently, the drawings present a very large variability. Therefore, comics image analysis is not a trivial problem and is still immature compared with other areas of application of image analysis and pattern recognition. Comics offer many challenges for researchers. For example, the detection and recognition of the characters in a comics page are not trivial since the main character can be a human being, an animal, or even an imaginary character. In this context, the “pattern recognition” task is a tricky problem. Comics analysis has aroused interest among researchers. The number of scientific papers dealing with comics analysis has significantly increased in international conferences and journals during the last ten years. The original approaches proposed in these papers in the area of computer vision, pattern recognition, and machine learning, show that comics analysis and understanding can be considered as a research topic. Moreover, the drawings of some comics are very similar to the ones of cartoons. So, some approaches can be applied to both media.
Title and abstract submission due: | May 7th, 2024 (updated!) |
Paper submission due: | May 7th, 2024 (updated!) |
Notification of acceptance: | May 27th, 2024 |
Camera-ready paper due: | June 10th, 2024 |
Workshop: | August 30th, 2024 |
Registration should be done via the 18th International Conference on Document Analysis and Recognition (ICDAR 2024) website.
See detail on ICDAR 2024 registration.
The deadline of the early bird fee is June 1st.
NOTE
eBDtheque consists of 100 images with ground truth for panels, speech balloons, tails, text lines, leading characters.
website: http://ebdtheque.univ-lr.fr/
Manga109 consists of over 20 thousand images of 109 volumes (21,142 images).
website: http://www.manga109.org/en/
All papers will have to be submitted through the EasyChair submission system on or before the submission deadline. Authors can update their papers before the submission deadline. MANPU 2024 will follow a single-blind review process. The accepted papers will be published in the "ICDAR pre-conference volume" edited by Springer in the Lecture Notes in Computer Science (LNCS) series.
Paper format and lengthPapers should be formatted with the style files/details available at Information for Authors of Springer Computer Science Proceedings. The LaTeX template for LNCS can be downloaded here. It is also available on Overleaf. Only PDF files are accepted. A complete paper should be submitted in the proper format. Papers accepted for the workshop will be allocated up to 15 pages (usually not counting references) in the proceedings. Submissions are expected to be in the range of 10-15 pages.
NotesPapers should describe original work on an MANPU-related topic. By submitting a manuscript to MANPU 2024, authors acknowledge that it has not been previously published or accepted for publication in substantially similar form in any peer-reviewed venue including journals or conferences. Also authors confirm that no paper substantially similar in content has been or will be submitted to another conference or workshop during the review period. The acceptance of a paper to MANPU 2024 requires that at least one of the authors registers for the workshop and presents the paper there. MANPU 2024 does not allow submission of any additional supplementary file.
Submission sitePaper submissions for MANPU2024 will be handled through the Easy Chair conference management system. Please visit https://www.easychair.org/conferences/?conf=manpu2024.
While sequential images are pervasive in society, from picture books to instruction manuals and storyboards, they appear most complex in comics around the world. Over the past two decades, an increasing focus on corpus analysis has begun to allow greater insights into how comics are structured and comprehended, across work blending manual and computational annotations. Here I will focus on the insights from two corpus projects: the Visual Language Research Corpus (360 comics, 9 countries, 48,000 panels) and the TINTIN Corpus (1,030 comics, 144 countries/territories, 76,000 panels). This analysis will highlight how the structures of comics change over time while interacting with the culture and languages of their authors, revealing distinctive “visual languages” that balance diverse and universal features, consistent with other linguistic systems.
Keynote speaker's BioNeil Cohn is an American cognitive scientist best known for his pioneering research on the overlap in cognition between graphic communication and language. He is the author of 2 graphic novels, over 100 academic papers, and 5 academic books, including his most recent, The Patterns of Comics (2024) and A Multimodal Language Faculty (2024). He is an Associate Professor at the Department of Cognition and Communication at Tilburg University in The Netherlands. His work can be found online at www.visuallanguagelab.com.
Opening 9:00 - 9:15 |
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Keynote speech 9:15 - 10:45 |
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The patterns of global comics Neil Cohn (Tilburg University, Netherlands) |
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Coffee break 10:45 - 11:15 |
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Oral Session 1 : Comic Understanding 11:15 - 12:45 |
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ComicBERT: A Transformer Model and Pre-training Strategy for Contextual Understanding in Comics Gürkan Soykan, Deniz Yuret and Tevfik Metin Sezgin (Koç University, Türkiye), |
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Investigating Neural Networks and Transformer Models for Enhanced Comic Decoding Eleanna Kouletou (National Kapodistrian University of Athens, Greece), Vassilis Papavassiliou and Vassilis Katsouros (Athena Research Center, Greece), |
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Spatially Augmented Speech Bubble to Character Association via Comic Multi-Task Learning Gürkan Soykan, Deniz Yuret and Tevfik Metin Sezgin (Koç University, Türkiye), |
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Discussion 12:45 - 13:15 |
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Lunch break 13:15 - 14:15 |
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Oral Session 2 : Comic Utilization 14:15 - 15:45 |
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Comics Datasets Framework: Mix of Comics datasets for detection benchmarking Emanuele Vivoli (Computer Vision Center, UAB, Spain), Irene Campaioli, Mariateresa Nardoni, Niccolò Biondi, Marco Bertini (MICC, University of Florence, Italy) and Dimosthenis Karatzas (Computer Vision Center, UAB, Spain) |
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Toward accessible comics for blind and low vision readers Christophe Rigaud, Jean-Christophe Burie (L3i Laboratory, La Rochelle, France) and Samuel Petit (Comix AI, France) |
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Quantitative evaluation based on CLIP for methods inhibiting imitation of painting styles Motoi Iwata, Keito Okamoto and Koichi Kise (Osaka Metropolitan University, Japan) |
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Coffee break 15:45 - 16:15 |
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Oral Session 3 : Text Detection, Recognition and Analysis 16:15 - 17:15 |
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A Comprehensive Gold Standard and Benchmark for Comics Text Detection and Recognition Gürkan Soykan, Deniz Yuret and Tevfik Metin Sezgin (Koç University, Türkiye), |
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Retrieving and Analyzing Translations of American Newspaper Comics with Visual Evidence Jacob Murel and David Smith (Northeastern University, USA) |
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Conclusion & Closing 17:15 - 17:30 |
Jean-Christophe Burie | University of La Rochelle, France | |
Motoi Iwata | Osaka Metropolitan University, Japan | |
Yusuke Matsui | The University of Tokyo, Japan |
Rita Hartel | Paderborn University, Germany | |
Tien-Tsin Wong | The Chinese University of Hong Kong, Hong Kong | |
Ryosuke Yamanishi | Kansai University, Japan |
Kiyoharu Aizawa | The University of Tokyo, Japan | |
Koichi Kise | Osaka Metropolitan University, Japan | |
Jean-Marc Ogier | University of La Rochelle, France | |
Toshihiko Yamasaki | The University of Tokyo, Japan |
Olivier Augerau | Ecole nationale d’ingénieurs de Brest, France | |
John Bateman | University of Bremen, Germany | |
Ying Cao | ShanghaiTech University, China | |
Wei-Ta Chu | National Chung Cheng University, Taiwan | |
Alexander Dunst | TU Dortmund University, Germany | |
Felix Giesa | Goethe University Frankfurt, Germany | |
Seiji Hotta | Tokyo University of Agriculture and Technology, Japan | |
Rynson W. H. Lau | City University of Hong Kong, Hong Kong | |
Jochen Laubrock | University of Potsdam, Germany | |
Tong-Yee Lee | National Cheng-Kung University, Taiwan | |
Chengze Li | St. Francis University, Hong Kong | |
Xueting Liu | The Chinese University of Hong Kong, Hong Kong | |
Muhammad Muzzamil Luqman | University of La Rochelle, France | |
Mitsunori Matsushita | Kansai University, Japan | |
Naoki Mori | Osaka Metropolitan University, Japan | |
Mitsuharu Nagamori | University of Tsukuba, Japan | |
Satoshi Nakamura | Meiji University, Japan | |
Frédéric Rayar | Tours University, France | |
Christophe Rigaud | University of La Rochelle, France | |
Yasuyuki Sumi | Future University Hakodate, Japan | |
Miki Ueno | The Kyoto College of Graduate Studies for Informatics, Japan | |
Emanuele Vivoli | CVC, Autonomous University of Barcelona, Spain | |
John Walsh | Indiana University, USA | |
Minshan Xie | The Chinese University of Hong Kong, Hong Kong | |
Lvmin Zhang | Stanford University, USA |
Endorsed by IAPR |