TY  - CONF
AU  - Sanket Biswas
AU  - Pau Riba
AU  - Josep Llados
AU  - Umapada Pal
PY  - 2021//
TI  - Graph-Based Deep Generative Modelling for Document Layout Generation
T2  - LNCS
BT  - 16th International Conference on Document Analysis and Recognition
SP  - 525
EP  - 537
VL  - 12917
N2  - One of the major prerequisites for any deep learning approach is the availability of large-scale training data. When dealing with scanned document images in real world scenarios, the principal information of its content is stored in the layout itself. In this work, we have proposed an automated deep generative model using Graph Neural Networks (GNNs) to generate synthetic data with highly variable and plausible document layouts that can be used to train document interpretation systems, in this case, specially in digital mailroom applications. It is also the first graph-based approach for document layout generation task experimented on administrative document images, in this case, invoices.
UR  - https://link.springer.com/chapter/10.1007/978-3-030-86159-9_38
L1  - http://refbase.cvc.uab.es/files/BRL2021.pdf
UR  - http://dx.doi.org/10.1007/978-3-030-86159-9_38
N1  - DAG; 600.121; 600.140; 110.312
ID  - Sanket Biswas2021
ER  -