Abstract Historical census records convey information that is key to perform genealogical research and demographic studies. Given the large number of documents of this type that exist, it is crucial to research methods that allow the automatic extraction of information from this type of document. In this work, we present a new corpus of this kind, comprising 535 historical census tables from French archives. Alongside this dataset, we have assessed three different baseline methods for information extraction. The first two methods employ a traditional sequential approach, where table rows are detected before extracting information. The third baseline uses an end-to-end model that directly extracts information from the table images without prior row detection. Our results demonstrate the effectiveness of all three baselines in tackling the information extraction task.