TY  - CONF
AU  - Jordy Van Landeghem
AU  - Ruben Tito
AU  - Lukasz Borchmann
AU  - Michal Pietruszka
AU  - Pawel Joziak
AU  - Rafal Powalski
AU  - Dawid Jurkiewicz
AU  - Mickael Coustaty
AU  - Bertrand Anckaert
AU  - Ernest Valveny
AU  - Matthew Blaschko
AU  - Sien Moens
AU  - Tomasz Stanislawek
A2  - ICCV
PY  - 2023//
TI  - Document Understanding Dataset and Evaluation (DUDE)
BT  - 20th IEEE International Conference on Computer Vision
SP  - 19528
EP  - 19540
N2  - We call on the Document AI (DocAI) community to re-evaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks. Document Understanding Dataset and Evaluation (DUDE) seeks to remediate the halted research progress in understanding visually-rich documents (VRDs). We present a new dataset with novelties related to types of questions, answers, and document layouts based on multi-industry, multi-domain, and multi-page VRDs of various origins and dates. Moreover, we are pushing the boundaries of current methods by creating multi-task and multi-domain evaluation setups that more accurately simulate real-world situations where powerful generalization and adaptation under low-resource settings are desired. DUDE aims to set a new standard as a more practical, long-standing benchmark for the community, and we hope that it will lead to future extensions and contributions that address real-world challenges. Finally, our work illustrates the importance of finding more efficient ways to model language, images, and layout in DocAI.
UR  - https://openaccess.thecvf.com/content/ICCV2023/html/Van_Landeghem_Document_Understanding_Dataset_and_Evaluation_DUDE_ICCV_2023_paper.html
L1  - http://refbase.cvc.uab.es/files/LTB2023.pdf
N1  - DAG
ID  - Jordy Van Landeghem2023
ER  -