Fetch-A-Set: A Large-Scale OCR-Free Benchmark for Historical Document Retrieval
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866929387829460992 |
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| author | Molina, Adrià Terrades, Oriol Ramos Lladós, Josep |
| author_facet | Molina, Adrià Terrades, Oriol Ramos Lladós, Josep |
| contents | This paper introduces Fetch-A-Set (FAS), a comprehensive benchmark tailored for legislative historical document analysis systems, addressing the challenges of large-scale document retrieval in historical contexts. The benchmark comprises a vast repository of documents dating back to the XVII century, serving both as a training resource and an evaluation benchmark for retrieval systems. It fills a critical gap in the literature by focusing on complex extractive tasks within the domain of cultural heritage. The proposed benchmark tackles the multifaceted problem of historical document analysis, including text-to-image retrieval for queries and image-to-text topic extraction from document fragments, all while accommodating varying levels of document legibility. This benchmark aims to spur advancements in the field by providing baselines and data for the development and evaluation of robust historical document retrieval systems, particularly in scenarios characterized by wide historical spectrum. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_07315 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fetch-A-Set: A Large-Scale OCR-Free Benchmark for Historical Document Retrieval Molina, Adrià Terrades, Oriol Ramos Lladós, Josep Information Retrieval Computer Vision and Pattern Recognition This paper introduces Fetch-A-Set (FAS), a comprehensive benchmark tailored for legislative historical document analysis systems, addressing the challenges of large-scale document retrieval in historical contexts. The benchmark comprises a vast repository of documents dating back to the XVII century, serving both as a training resource and an evaluation benchmark for retrieval systems. It fills a critical gap in the literature by focusing on complex extractive tasks within the domain of cultural heritage. The proposed benchmark tackles the multifaceted problem of historical document analysis, including text-to-image retrieval for queries and image-to-text topic extraction from document fragments, all while accommodating varying levels of document legibility. This benchmark aims to spur advancements in the field by providing baselines and data for the development and evaluation of robust historical document retrieval systems, particularly in scenarios characterized by wide historical spectrum. |
| title | Fetch-A-Set: A Large-Scale OCR-Free Benchmark for Historical Document Retrieval |
| topic | Information Retrieval Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2406.07315 |