{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:56:49Z","timestamp":1779382609886,"version":"3.53.1"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031706417","type":"print"},{"value":"9783031706424","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-70642-4_9","type":"book-chapter","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T18:02:18Z","timestamp":1725991338000},"page":"140-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Image-to-Image Translation Approach for\u00a0Page Layout Analysis and\u00a0Artificial Generation of\u00a0Historical Manuscripts"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1567-6508","authenticated-orcid":false,"given":"Chahan","family":"Vidal-Gor\u00e8ne","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0385-7037","authenticated-orcid":false,"given":"Jean-Baptiste","family":"Camps","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"9_CR1","doi-asserted-by":"crossref","unstructured":"Arroyo, D.M., Postels, J., Tombari, F.: Variational transformer networks for layout generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13642\u201313652 (2021)","DOI":"10.1109\/CVPR46437.2021.01343"},{"issue":"7900","key":"9_CR2","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1038\/s41586-022-04448-z","volume":"603","author":"Y Assael","year":"2022","unstructured":"Assael, Y., et al.: Restoring and attributing ancient texts using deep neural networks. Nature 603(7900), 280\u2013283 (2022)","journal-title":"Nature"},{"key":"9_CR3","doi-asserted-by":"crossref","unstructured":"Barrere, K., Soullard, Y., Lemaitre, A., Co\u00fcasnon, B.: Training transformer architectures on few annotated data: an application to historical handwritten text recognition. Int. J. Doc. Anal. Recogn. (IJDAR), pp. 1\u201314 (2024)","DOI":"10.1007\/s10032-023-00459-2"},{"key":"9_CR4","doi-asserted-by":"publisher","unstructured":"Binmakhashen, G.M., Mahmoud, S.A.: Document layout analysis: a comprehensive survey. ACM Comput. Surv. 52(6), 109:1\u2013109:36 (2019). https:\/\/doi.org\/10.1145\/3355610","DOI":"10.1145\/3355610"},{"key":"9_CR5","unstructured":"Biswas, S., Banerjee, A., Llad\u00f3s, J., Pal, U.: DocSegTr: an instance-level end-to-end document image segmentation transformer. arXiv preprint arXiv:2201.11438 (2022)"},{"key":"9_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1007\/978-3-030-86334-0_36","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021","author":"S Biswas","year":"2021","unstructured":"Biswas, S., Riba, P., Llad\u00f3s, J., Pal, U.: DocSynth: a layout guided approach for controllable document image synthesis. In: Llad\u00f3s, J., Lopresti, D., Uchida, S. (eds.) ICDAR 2021. LNCS, vol. 12823, pp. 555\u2013568. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86334-0_36"},{"key":"9_CR7","unstructured":"Cl\u00e9rice, T.: Ground-truth free evaluation of HTR on old French and Latin medieval literary manuscripts. In: Computational Humanities Research Conference (CHR) 2022 (2022)"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Cl\u00e9rice, T.: You actually look twice at it (YALTAi): using an object detection approach instead of region segmentation within the Kraken engine. J. Data Min. Digit. Human. (2023)","DOI":"10.46298\/jdmdh.9806"},{"key":"9_CR9","doi-asserted-by":"publisher","unstructured":"Diem, M., Kleber, F., Fiel, S., Gr\u00fcning, T., Gatos, B.: cBAD: ICDAR2017 competition on baseline detection. In: ICDAR 2017 \u2013 14th International Conference on Document Analysis and Recognition, vol.\u00a001, pp. 1355\u20131360 (2017). https:\/\/doi.org\/10.1109\/ICDAR.2017.222","DOI":"10.1109\/ICDAR.2017.222"},{"key":"9_CR10","doi-asserted-by":"publisher","unstructured":"Diem, M., Kleber, F., Sablatnig, R., Gatos, B.: cBAD: ICDAR2019 competition on baseline detection. In: ICDAR 2019 \u2013 15th International Conference on Document Analysis and Recognition, pp. 1494\u20131498 (2019). https:\/\/doi.org\/10.1109\/ICDAR.2019.00240","DOI":"10.1109\/ICDAR.2019.00240"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Fogel, S., Averbuch-Elor, H., Cohen, S., Mazor, S., Litman, R.: ScrabbleGAN: semi-supervised varying length handwritten text generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4324\u20134333 (2020)","DOI":"10.1109\/CVPR42600.2020.00438"},{"key":"9_CR12","unstructured":"Gabay, S., Camps, J.B., Pinche, A., Jahan, C.: SegmOnto: common vocabulary and practices for analysing the layout of manuscripts (and more). In: 1st International Workshop on Computational Paleography (IWCP@ ICDAR 2021) (2021)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Gr\u00fcning, T., Labahn, R., Diem, M., Kleber, F., Fiel, S.: Read-bad: a new dataset and evaluation scheme for baseline detection in archival documents. In: 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), pp. 351\u2013356. IEEE (2018)","DOI":"10.1109\/DAS.2018.38"},{"issue":"3","key":"9_CR14","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1007\/s10032-019-00332-1","volume":"22","author":"T Gr\u00fcning","year":"2019","unstructured":"Gr\u00fcning, T., Leifert, G., Strau\u00df, T., Michael, J., Labahn, R.: A two-stage method for text line detection in historical documents. Int. J. Doc. Anal. Recogn. (IJDAR) 22(3), 285\u2013302 (2019)","journal-title":"Int. J. Doc. Anal. Recogn. (IJDAR)"},{"key":"9_CR15","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: GANs trained by a two time-scale update rule converge to a local NASH equilibrium. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"9_CR16","doi-asserted-by":"publisher","unstructured":"Hoyez, H., Schockaert, C., Rambach, J., Mirbach, B., Stricker, D.: Unsupervised image-to-image translation: a review. Sensors 22(21) (2022). https:\/\/doi.org\/10.3390\/s22218540, https:\/\/www.mdpi.com\/1424-8220\/22\/21\/8540","DOI":"10.3390\/s22218540"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"9_CR18","doi-asserted-by":"crossref","unstructured":"Kahle, P., Colutto, S., Hackl, G., M\u00fchlberger, G.: Transkribus - a service platform for transcription, recognition and retrieval of historical documents. In: ICDAR 2017 \u2013 14th International Conference on Document Analysis and Recognition, vol.\u00a04, pp. 19\u201324. IEEE (2017)","DOI":"10.1109\/ICDAR.2017.307"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Kiessling, B., Ezra, D.S.B., Miller, M.T.: BADAM: a public dataset for baseline detection in Arabic-script manuscripts. In: Proceedings of the 5th International Workshop on Historical Document Imaging and Processing, pp. 13\u201318 (2019)","DOI":"10.1145\/3352631.3352648"},{"key":"9_CR20","doi-asserted-by":"crossref","unstructured":"Kiessling, B., Tissot, R., Stokes, P., Ezra, D.S.B.: eScriptorium: an open source platform for historical document analysis. In: ICDAR 2019 \u2013 15th International Conference on Document Analysis and Recognition, Workshops (ICDARW), vol.\u00a02, pp. 19\u201319. IEEE (2019)","DOI":"10.1109\/ICDARW.2019.10032"},{"issue":"3","key":"9_CR21","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s10032-023-00439-6","volume":"26","author":"B Madi","year":"2023","unstructured":"Madi, B., Alaasam, R., Shammas, R., El-Sana, J.: Scheme for palimpsests reconstruction using synthesized dataset. Int. J. Doc. Anal. Recogn. (IJDAR) 26(3), 211\u2013222 (2023)","journal-title":"Int. J. Doc. Anal. Recogn. (IJDAR)"},{"key":"9_CR22","doi-asserted-by":"crossref","unstructured":"Monnier, T., Aubry, M.: docExtractor: an off-the-shelf historical document element extraction. In: 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 91\u201396. IEEE (2020)","DOI":"10.1109\/ICFHR2020.2020.00027"},{"key":"9_CR23","doi-asserted-by":"publisher","unstructured":"Muehlberger, G., Hackl, G.: NewsEye\/READ OCR training dataset from French Newspapers (18th, 19th, early 20th C.) (2020). https:\/\/doi.org\/10.5281\/zenodo.4293602","DOI":"10.5281\/zenodo.4293602"},{"key":"9_CR24","unstructured":"Najem-Meyer, S., Romanello, M.: Page layout analysis of text-heavy historical documents: a comparison of textual and visual approaches. In: Proceedings of the Computational Humanities Research Conference 2022 Antwerp, Belgium, 12\u201314 December 2022, pp. 36\u201354 (2022)"},{"issue":"4","key":"9_CR25","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s10032-022-00405-8","volume":"25","author":"K Nikolaidou","year":"2022","unstructured":"Nikolaidou, K., Seuret, M., Mokayed, H., Liwicki, M.: A survey of historical document image datasets. Int. J. Doc. Anal. Recogn. (IJDAR) 25(4), 305\u2013338 (2022)","journal-title":"Int. J. Doc. Anal. Recogn. (IJDAR)"},{"key":"9_CR26","doi-asserted-by":"crossref","unstructured":"Oliveira, S.A., Seguin, B., Kaplan, F.: dhSegment: a generic deep-learning approach for document segmentation. In: 2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 7\u201312. IEEE (2018)","DOI":"10.1109\/ICFHR-2018.2018.00011"},{"key":"9_CR27","doi-asserted-by":"publisher","first-page":"3859","DOI":"10.1109\/TMM.2021.3109419","volume":"24","author":"Y Pang","year":"2021","unstructured":"Pang, Y., Lin, J., Qin, T., Chen, Z.: Image-to-image translation: methods and applications. IEEE Trans. Multimedia 24, 3859\u20133881 (2021)","journal-title":"IEEE Trans. Multimedia"},{"key":"9_CR28","doi-asserted-by":"crossref","unstructured":"Pfitzmann, B., Auer, C., Dolfi, M., Nassar, A.S., Staar, P.: DocLayNet: a large human-annotated dataset for document-layout segmentation. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 3743\u20133751 (2022)","DOI":"10.1145\/3534678.3539043"},{"key":"9_CR29","unstructured":"Pinche, A.: Cremma Medieval (2022). https:\/\/github.com\/HTR-United\/cremma-medieval"},{"key":"9_CR30","doi-asserted-by":"crossref","unstructured":"Pisaneschi, L., Gemelli, A., Marinai, S.: Automatic generation of scientific papers for data augmentation in document layout analysis. Pattern Recogn. Lett. 167, 38\u201344 (2023)","DOI":"10.1016\/j.patrec.2023.01.018"},{"key":"9_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1007\/978-3-031-41679-8_21","volume-title":"Document Analysis and Recognition - ICDAR 2023","author":"A Poddar","year":"2023","unstructured":"Poddar, A., Dey, S., Jawanpuria, P., Mukhopadhyay, J., Kumar Biswas, P.: TBM-GAN: synthetic document generation with degraded background. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds.) ICDAR 2023. LNCS, vol. 14188, pp. 366\u2013383. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-41679-8_21"},{"key":"9_CR32","unstructured":"Quir\u00f3s, L.: Multi-task handwritten document layout analysis. arXiv preprint arXiv:1806.08852 (2018)"},{"key":"9_CR33","doi-asserted-by":"crossref","unstructured":"de\u00a0Sousa\u00a0Neto, A.F., Bezerra, B.L.D., de\u00a0Moura, G.C.D., Toselli, A.H.: Data augmentation for offline handwritten text recognition: a systematic literature review. SN Comput. Sci. 5(2), 258 (2024)","DOI":"10.1007\/s42979-023-02583-6"},{"key":"9_CR34","doi-asserted-by":"publisher","unstructured":"Stoekl Ben\u00a0Ezra, D., Brown-DeVost, B., Jablonski, P., Lapin, H., Kiessling, B., Lolli, E.: BiblIA - a general model for medieval hebrew manuscripts and an open annotated dataset. In: The 6th International Workshop on Historical Document Imaging and Processing. HIP \u201921, pp. 61\u201366. Association for Computing Machinery, New York, NY, USA (2021). https:\/\/doi.org\/10.1145\/3476887.3476896","DOI":"10.1145\/3476887.3476896"},{"key":"9_CR35","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1007\/978-3-031-41682-8_27","volume-title":"Document Analysis and Recognition - ICDAR 2023","author":"N Tanveer","year":"2023","unstructured":"Tanveer, N., Ul-Hasan, A., Shafait, F.: Diffusion models for document image generation. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds.) ICDAR 2023. LNCS, vol. 14189, pp. 438\u2013453. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-41682-8_27"},{"key":"9_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1007\/978-3-031-51026-7_40","volume-title":"Image Analysis and Processing - ICIAP 2023 Workshops","author":"C Vidal-Gor\u00e8ne","year":"2023","unstructured":"Vidal-Gor\u00e8ne, C., Camps, J.B., Cl\u00e9rice, T.: Synthetic lines from historical manuscripts: an experiment using GAN and style transfer. In: Foresti, G.L., Fusiello, A., Hancock, E. (eds.) ICIAP 2023. LNCS, vol. 14366, pp. 477\u2013488. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-51026-7_40"},{"key":"9_CR37","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/978-3-030-86334-0_33","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021","author":"C Vidal-Gor\u00e8ne","year":"2021","unstructured":"Vidal-Gor\u00e8ne, C., Dupin, B., Decours-Perez, A., Riccioli, T.: A modular and automated annotation platform for handwritings: evaluation on under-resourced languages. In: Llad\u00f3s, J., Lopresti, D., Uchida, S. (eds.) ICDAR 2021. LNCS, vol. 12823, pp. 507\u2013522. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86334-0_33"},{"key":"9_CR38","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/978-3-030-86198-8_19","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021 Workshops","author":"C Vidal-Gor\u00e8ne","year":"2021","unstructured":"Vidal-Gor\u00e8ne, C., Lucas, N., Salah, C., Decours-Perez, A., Dupin, B.: RASAM \u2013 a dataset for the recognition and analysis of scripts in Arabic Maghrebi. In: Barney Smith, E.H., Pal, U. (eds.) ICDAR 2021. LNCS, vol. 12916, pp. 265\u2013281. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86198-8_19"},{"key":"9_CR39","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1007\/978-3-030-86334-0_40","volume-title":"Document Analysis and Recognition \u2013 ICDAR 2021","author":"L V\u00f6gtlin","year":"2021","unstructured":"V\u00f6gtlin, L., Drazyk, M., Pondenkandath, V., Alberti, M., Ingold, R.: Generating synthetic handwritten historical documents with OCR constrained GANs. In: Llad\u00f3s, J., Lopresti, D., Uchida, S. (eds.) ICDAR 2021. LNCS, vol. 12823, pp. 610\u2013625. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86334-0_40"},{"key":"9_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1007\/978-3-031-41685-9_19","volume-title":"Document Analysis and Recognition - ICDAR 2023","author":"H Wang","year":"2023","unstructured":"Wang, H., Wang, Y., Wei, H.: Affganwriting: a handwriting image generation method based on multi-feature fusion. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds.) ICDAR 2023. LNCS, vol. 14190, pp. 302\u2013312. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-41685-9_19"},{"key":"9_CR41","doi-asserted-by":"crossref","unstructured":"Xu, Y., Li, M., Cui, L., Huang, S., Wei, F., Zhou, M.: LayoutLM: pre-training of text and layout for document image understanding. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1192\u20131200 (2020)","DOI":"10.1145\/3394486.3403172"},{"key":"9_CR42","doi-asserted-by":"crossref","unstructured":"Zhong, X., Tang, J., Yepes, A.J.: Publaynet: largest dataset ever for document layout analysis. In: 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 1015\u20131022. IEEE (2019)","DOI":"10.1109\/ICDAR.2019.00166"}],"container-title":["Lecture Notes in Computer Science","Document Analysis and Recognition \u2013 ICDAR 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70642-4_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T23:48:35Z","timestamp":1732751315000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70642-4_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031706417","9783031706424"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70642-4_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"11 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICDAR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Document Analysis and Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icdar2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icdar2024.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}