In this representation, the vertexes and edges of the grid store the localization and adjacency information of the table.
A novel weakly supervised learning method is proposed to enable the network to be trained using only transcript annotations; thus, the expensive character segmentation annotations required by previous segmentation-based methods can be avoided.
Automatic font generation remains a challenging research issue due to the large amounts of characters with complicated structures.
Visual information extraction (VIE) has attracted increasing attention in recent years.
For building a robust point detector, a fully convolutional network with feature fusion module is adopted, which can distinguish close points compared to traditional methods.
In this framework, two branches named character branch and layout branch are added behind the feature extraction network.