{"id":71,"date":"2019-01-12T16:18:06","date_gmt":"2019-01-12T15:18:06","guid":{"rendered":"https:\/\/iapr-tc10.univ-lr.fr\/?page_id=71"},"modified":"2026-04-13T14:02:35","modified_gmt":"2026-04-13T13:02:35","slug":"datasets","status":"publish","type":"page","link":"https:\/\/iapr-tc10.univ-lr.fr\/?page_id=71","title":{"rendered":"Datasets\/Softwares"},"content":{"rendered":"\n<h4>Circuit diagram:<\/h4>\n\n\n\n<ul>\n<li><a href=\"http:\/\/dae.cse.lehigh.edu\/DAE\/?q=browse\/dataitem\/606796\">Bethlehem Steel Dataset<\/a> (in collaboration with Lehigh University)<\/li>\n\n\n\n<li><a href=\"https:\/\/osf.io\/ju9ck\/\">CircuitGraphHandDrawn<\/a>: handwritten circuit diagram (<a href=\"https:\/\/arxiv.org\/pdf\/2107.10373.pdf\">paper<\/a>)<\/li>\n<\/ul>\n\n\n\n<h4>Floor plan:<\/h4>\n\n\n\n<ul>\n<li><a href=\"https:\/\/www.researchgate.net\/publication\/336603377_BRIDGE_Building_Plan_Repository_for_Image_Description_Generation_and_Evaluation\">BRIDGE<\/a>: Building Plan Repository for Image Description Generation, and Evaluation (<a rel=\"noreferrer noopener\" href=\"https:\/\/www.researchgate.net\/publication\/336603377_BRIDGE_Building_Plan_Repository_for_Image_Description_Generation_and_Evaluation\" target=\"_blank\">paper<\/a>)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/dag.cvc.uab.es\/resources\/floorplans\/\" target=\"_blank\">CVC-FP<\/a> (Database for structural floor plan analysis)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/www.cvc.uab.es\/~marcal\/FPLAN-POLY\/index.html\" target=\"_blank\">FPLAN-POLY dataset<\/a> of vectorized graphic documents (floorplans)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/mathieu.delalandre.free.fr\/projects\/sesyd\/\" target=\"_blank\">SESYD<\/a>: Systems Evaluation SYnthetic Documents11 types of synthetic documents (<a href=\"http:\/\/mathieu.delalandre.free.fr\/publications\/IJDAR2010.pdf\">paper<\/a>)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/rit.rakuten.com\/data_release\/\" target=\"_blank\">R-FP-500<\/a>: Floor plan from Rakuten Real Estate and pixel-wise wall label (by Rakuten Institute of Technology)<\/li>\n<\/ul>\n\n\n\n<p><strong>Maps\/cadastral:<\/strong><\/p>\n\n\n\n<ul>\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/corpora.kiv.zcu.cz\/map_border\/\" target=\"_blank\">Map Border Dataset<\/a>: dataset for Detection and Segmentation tasks in Historical Cadastral Maps<\/li>\n<\/ul>\n\n\n\n<h4>Music Scores: <\/h4>\n\n\n\n<ul>\n<li><a rel=\"noreferrer noopener\" aria-label=\"List of Music Scores datasets (opens in a new tab)\" href=\"https:\/\/apacha.github.io\/OMR-Datasets\/\" target=\"_blank\">List of Music Scores datasets<\/a><\/li>\n\n\n\n<li>ICDAR\/GREC competitions on music scores (<a rel=\"noreferrer noopener\" aria-label=\"CVC-MUSCIMA (opens in a new tab)\" href=\"http:\/\/www.cvc.uab.es\/cvcmuscima\/\" target=\"_blank\">CVC-MUSCIMA<\/a>)<\/li>\n<\/ul>\n\n\n\n<h4 id=\"comic-book-datasets\">Comic book:<\/h4>\n\n\n\n<ul>\n<li><a href=\"https:\/\/github.com\/IVRL\/AI4VA\">AI4VA<\/a>: AI for Visual Arts dataset comprising comic-style imagery sourced from two mid-twentieth-century Franco-Belgian comics series, Placid et Muzo and Yves le loup for VLM benchmarking (<a href=\"https:\/\/arxiv.org\/abs\/2410.20459\">arXiv<\/a>, 2024).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/sites.google.com\/view\/banglacomicbookdataset\" target=\"_blank\">BCBID<\/a>: Bangla Comic Book Image Dataset contains a total of 3327 images of different kinds of &#8216;Bengali Comic Books&#8217; from a diverse set of renowned authors (published at ICDAR 2019).<\/li>\n\n\n\n<li><a href=\"https:\/\/c3b-benchmark.github.io\/\">C3B<\/a>: Comics Cross-Cultural Benchmark, a multicultural, multitask and multilingual cultural awareness capabilities benchmark. Comprises over 2000 images and over 18000 QA pairs (<a href=\"https:\/\/arxiv.org\/abs\/2510.00041v1\">arXiv<\/a>, 2025).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/sherleens\/Comics\" target=\"_blank\">CDVSR<\/a>: Comics Dataset for Visual Sentiment Recognition, 10,281\u200b images of comic and manga.<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/daydayup586\/ChrOMIC\">ChrOMIC<\/a>: Chronological Reasoning in Multi-panel Comics is the first benchmark designed to evaluate vision-language models (VLMs) on their ability to understand panel ordering and narrative reasoning in comics (<a href=\"https:\/\/aclanthology.org\/2026.eacl-long.205.pdf\">EACL 2026<\/a>).<\/li>\n\n\n\n<li><a href=\"https:\/\/aclanthology.org\/2023.acl-long.791\/\">ComSet<\/a>: 54K strips, harvested from 13 popular comics available online.<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/martinekj\/comic-dacts\/tree\/main\">COMICORDA<\/a>: A Novel Dataset for Dialogue Act Recognition in Comics, an extension of the EmoRecCom dataset.<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/obj.umiacs.umd.edu\/comics\/index.html\" target=\"_blank\">COMICS<\/a>: 1.2 million panels paired with automatic textbox transcriptions from Golden Age collection of the <a href=\"https:\/\/digitalcomicmuseum.com\/\">Digital Comics Museum<\/a> (published at CVPR 2017). New OCRed text <em><a href=\"https:\/\/link.springer.com\/chapter\/10.1007\/978-3-031-70645-5_12\">COMICS Text+<\/a><\/em> (2024).<\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/abs\/2407.03540\">Comics Datasets Framework<\/a>: Mix of Comics datasets for detection benchmarking  (ICDAR 2024)<\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/abs\/2503.08561\">ComicsPAP<\/a>: understanding comic strips by picking the correct panel (arXiv 2025)<\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/pdf\/2508.16190v1\">ComicScene154<\/a>: focuses on scene-level narrative arcs annotation. It comprises four public-domain comic magazines containing 34 distinct stories that span a total of 154 pages from Golden Age public-domain American comics (<a href=\"https:\/\/arxiv.org\/pdf\/2508.16190v1\">arXiv<\/a>, <a href=\"https:\/\/github.com\/Knorrsche\/ComicScene154\/tree\/main\">link<\/a>).<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/ku21fan\/COO-Comic-Onomatopoeia\">COO<\/a>: COmic Onomatopoeia dataset for recognizing arbitrary or truncated texts. Based on Manga109 images, it consists of 61,465 polygons and 2,261 links between truncated texts (<a href=\"https:\/\/arxiv.org\/abs\/2207.04675\">ECCV 2022<\/a>)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/gitlab.univ-lr.fr\/crigau02\/dcm-dataset\" target=\"_blank\">DCM772<\/a>: 772 annotated images from 27 Golden Age collection of the <a rel=\"noreferrer noopener\" href=\"https:\/\/digitalcomicmuseum.com\/\" target=\"_blank\">Digital Comics Museum<\/a>. It includes ground-truth bounding boxes of all panels, all characters (body + faces), small or big, human-like or animal-like (published at MDPI Journal Imaging 2018).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/ebdtheque.univ-lr.fr\/database\/\" target=\"_blank\">eBDtheque<\/a>: a representative database of comics of 100 pages including manual annotations of 850 panels and 1092 balloons paired with 1620 comic characters and 4693 text lines. (published at ICDAR 2013).<\/li>\n\n\n\n<li>EmoComics35: a genre-diverse dataset consisting of 35 comic albums where utterances are annotated with character identity and fine-grained multi-class emotion labels (ICPR2026).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/emoreccom.univ-lr.fr\/\" target=\"_blank\">EmoRecCom<\/a>: ICDAR2021 Competition Multimodal Emotion Recognition on Comics scenes (<a rel=\"noreferrer noopener\" href=\"https:\/\/competitions.codalab.org\/competitions\/?q=Multimodal+Emotion+Recognition+on+Comics+scenes\" target=\"_blank\">codalab<\/a>)  (ICDAR 2021).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/fgc.univ-lr.fr\/task\/\" target=\"_blank\">FGC 2019<\/a>: ICDAR 2019 Competition on Fine-Grained Classification of Comic Characters<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/groups.uni-paderborn.de\/graphic-literature\/gncorpus\/corpus.php\" target=\"_blank\">GNC<\/a>: the Graphic Narrative Corpus currently contains textual metadata of about 219 titles written in English. Corresponding image are not provided due to copyright issue (ICDAR 2017).<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/luxiangju-PersonAI\/iCartoonFace\">iCartoonFace<\/a>: a large-scale challenging dataset established for cartoon face recognition. 389,678 images of 5,013 cartoon persons collected from 1,302 cartoon albums (published at ICM 2020).<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/gesstalt\/IMCDB\" target=\"_blank\">IMCDB<\/a>: Indian Mythological Comic Dataset &#8211; digitized Indian comic storybook in the English language (ICDAR 2021).<\/li>\n\n\n\n<li><a href=\"https:\/\/gitlab.univ-lr.fr\/jcburie\/kaboom_onomatopoeia_dataset\/-\/tree\/DATASET\" data-type=\"URL\" data-id=\"https:\/\/gitlab.univ-lr.fr\/jcburie\/kaboom_onomatopoeia_dataset\/-\/tree\/DATASET\">KABOOM ONOMATOPEA<\/a>: Comic Onomatopoeia Dataset for Extracting Arbitrary or Truncated Texts<\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/abs\/2510.07951\">Large-scale Dataset<\/a> for Robust Complex Anime Scene Text Detection: containing 735K images and 4.2M annotated text block position (<a href=\"https:\/\/arxiv.org\/abs\/2510.07951\">arXiv<\/a>)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"http:\/\/www.manga109.org\/en\/\" target=\"_blank\">Manga 109<\/a>: 109 manga volumes from <a href=\"http:\/\/www.mangaz.com\/\">\u201cManga Library Z\u201d<\/a> drawn by professional manga artists in Japan (published in  Multimedia Tools and Applications Journal 2017).<\/li>\n\n\n\n<li><a href=\"https:\/\/huggingface.co\/datasets\/MS92\/MangaSegmentation\">MangaSeg<\/a>: 700,000 segmentation annotations for 10,130 double-sided manga pages from Manga 109 dataset. Panels, characters, faces, speech balloons, texts, and links between characters and balloon annotated at the instance-level (<a href=\"https:\/\/openaccess.thecvf.com\/content\/CVPR2025\/papers\/Xie_Advancing_Manga_Analysis_Comprehensive_Segmentation_Annotations_for_the_Manga109_Dataset_CVPR_2025_paper.pdf\">CVPR 2025<\/a>).<\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/abs\/2407.19034\">MangaUB<\/a>: A Manga Understanding Benchmark for Large Multimodal Models (<a href=\"https:\/\/arxiv.org\/abs\/2407.19034\">IEEE MM<\/a>25)<\/li>\n\n\n\n<li><a href=\"https:\/\/huggingface.co\/datasets\/ragavsachdeva\/popmanga_test\">PopManga<\/a>: includes 57,318 images from 100 of the most popular English manga. However, the full dataset is not publicly available; only a small test set of 1,925 images, collected from Manga Plus by Shueisha 2, has been released. Contains detection annotations and text-character and character-character links for dialog transcription (<a href=\"https:\/\/arxiv.org\/abs\/2401.10224\">CVPR 2024<\/a>).<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/mantra-inc\/open-mantra-dataset?tab=readme-ov-file\">OpenMantra<\/a>: evaluation dataset of 5 manga titles (JA\/EN\/ZH text+images) for machine translation, presented in <a href=\"https:\/\/arxiv.org\/abs\/2012.14271\">AAAI 2021<\/a>.<\/li>\n\n\n\n<li><a href=\"https:\/\/re-verse.vercel.app\/\">Re:Verse<\/a>: a comprehensive benchmark designed to evaluate VLMs\u2019 ability to understand long-form manga narratives (<a href=\"https:\/\/arxiv.org\/abs\/2508.08508v3\">ICCV 2025<\/a>).<\/li>\n\n\n\n<li><a href=\"https:\/\/bitbucket.org\/l3ivan\/sequencity612\/src\/master\/\">Sequencity612<\/a>: comic character annotation for all characters, small or big, speaking or not and in the background on 612 recent comic book pages (<a href=\"https:\/\/ieeexplore.ieee.org\/document\/8270235\">ICDAR 2017<\/a>)<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" aria-label=\"SSGCI 2016 (opens in a new tab)\" href=\"http:\/\/ssgci.univ-lr.fr\" target=\"_blank\">SSGCI 2016<\/a> ICPR 2016 Competition on Subgraph Spotting in Graph representation of Comic Book Images<\/li>\n\n\n\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/www.visuallanguagelab.com\/vlrc\" target=\"_blank\">VLRC<\/a>: Visual Language Research Corpus made up of ~36,000 coded panels from 300+ comics from Europe, Asia, and the United States, across time periods (1940-present), and various genres.<\/li>\n\n\n\n<li><a href=\"https:\/\/github.com\/yangqi1725\/YManga\">YManga<\/a>: 1,015 high-quality yonkoma-type manga strips (<a href=\"https:\/\/2024.emnlp.org\/\">EMNLP 2024<\/a>).<\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Circuit diagram: Floor plan: Maps\/cadastral: Music Scores: Comic book:<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":67,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_links_to":"","_links_to_target":""},"_links":{"self":[{"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/pages\/71"}],"collection":[{"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=71"}],"version-history":[{"count":61,"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/pages\/71\/revisions"}],"predecessor-version":[{"id":1892,"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/pages\/71\/revisions\/1892"}],"up":[{"embeddable":true,"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=\/wp\/v2\/pages\/67"}],"wp:attachment":[{"href":"https:\/\/iapr-tc10.univ-lr.fr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=71"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}