PT Journal
AU Sanket Biswas
   Pau Riba
   Josep Llados
   Umapada Pal
TI Beyond Document Object Detection: Instance-Level Segmentation of Complex Layouts
SO International Journal on Document Analysis and Recognition
JI IJDAR
PY 2021
BP 269–281
VL 24
DI 10.1007/s10032-021-00380-6
AB Information extraction is a fundamental task of many business intelligence services that entail massive document processing. Understanding a document page structure in terms of its layout provides contextual support which is helpful in the semantic interpretation of the document terms. In this paper, inspired by the progress of deep learning methodologies applied to the task of object recognition, we transfer these models to the specific case of document object detection, reformulating the traditional problem of document layout analysis. Moreover, we importantly contribute to prior arts by defining the task of instance segmentation on the document image domain. An instance segmentation paradigm is especially important in complex layouts whose contents should interact for the proper rendering of the page, i.e., the proper text wrapping around an image. Finally, we provide an extensive evaluation, both qualitative and quantitative, that demonstrates the superior performance of the proposed methodology over the current state of the art.
ER