Abstract: A document layout system for determining a layout of a document. The document layout system is configured to apply an OCR technique to identify the text in the document. The document layout system is further configured to generate a graph representation of the document, wherein the graph representation comprises a plurality of nodes and a plurality of edges that connect different ones of the plurality of nodes, wherein individual ones of the nodes correspond to different portions of the text. The document layout system is also configured to apply a graph cluster network machine learning model to the graph representation to identify a layout of different sections of the document according to respective merge inferences determined for individual ones of the plurality of edges. The document layout system is also configured to provide the layout of different sections of the document.

Abstract: Techniques for recognizing text in an image are described. An exemplary method may include receiving a request to recognize text in an image; extracting features from the image and generating a visual feature sequence from the extracted features; performing selective contextual refinement at least one selective contextual refinement block of a stack of selective contextual refinement blocks to generate a text prediction by: generating a contextual feature map and combining the contextual feature map with the visual feature sequence into a visual feature space, and applying a selective decoder that utilizes a two-step attention on the visual feature space to generate a text prediction, wherein the two-step attention includes performing a 1-D self-attention computation to generate attentional features and decoding the attentional features to generate the text prediction; and outputting the generated text prediction.