TY  - CONF
AU  - Stepan Simsa
AU  - Michal Uricar
AU  - Milan Sulc
AU  - Yash Patel
AU  - Ahmed Hamdi
AU  - Matej Kocian
AU  - Matyas Skalicky
AU  - Jiri Matas
AU  - Antoine Doucet
AU  - Mickael Coustaty
AU  - Dimosthenis Karatzas
A2  - CLEF
PY  - 2023//
TI  - Overview of DocILE 2023: Document Information Localization and Extraction
T2  - LNCS
BT  - International Conference of the Cross-Language Evaluation Forum for European Languages
SP  - 276–293
VL  - 14163
KW  - Information Extraction
KW  - Computer Vision
KW  - Natural Language Processing
KW  - Optical Character Recognition
KW  - Document Understanding
N2  - This paper provides an overview of the DocILE 2023 Competition, its tasks, participant submissions, the competition results and possible future research directions. This first edition of the competition focused on two Information Extraction tasks, Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR). Both of these tasks require detection of pre-defined categories of information in business documents. The second task additionally requires correctly grouping the information into tuples, capturing the structure laid out in the document. The competition used the recently published DocILE dataset and benchmark that stays open to new submissions. The diversity of the participant solutions indicates the potential of the dataset as the submissions included pure Computer Vision, pure Natural Language Processing, as well as multi-modal solutions and utilized all of the parts of the dataset, including the annotated, synthetic and unlabeled subsets.
UR  - https://link.springer.com/chapter/10.1007/978-3-031-42448-9_21
UR  - http://dx.doi.org/https://doi.org/10.1007/978-3-031-42448-9_21
N1  - DAG
ID  - Stepan Simsa2023
ER  -