19 citations · 25 across the 4 of their papers we have counts for
7 papers
Text and Style Conditioned GAN for Generation of Offline Handwriting Lines
Brian Davis, Chris Tensmeyer, Brian Price +3
This paper presents a GAN for generating images of handwritten lines conditioned on arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or singl…
Using Behavioral Interactions from a Mobile Device to Classify the Reader's Prior Familiarity and Goal Conditions
Sungjin Nam, Zoya Bylinskii, Christopher Tensmeyer +3
A student reads a textbook to learn a new topic; an attorney leafs through familiar legal documents. Each reader may have a different goal for, and prior knowledge of, their readin…
Cross-Domain Document Object Detection: Benchmark Suite and Method
Kai Li, Curtis Wigington, Chris Tensmeyer +6
Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like…
PageNet: Page Boundary Extraction in Historical Handwritten Documents
Chris Tensmeyer, Brian Davis, Curtis Wigington +2
When digitizing a document into an image, it is common to include a surrounding border region to visually indicate that the entire document is present in the image. However, this b…
Convolutional Neural Networks for Font Classification
Chris Tensmeyer, Daniel Saunders, Tony Martinez
Classifying pages or text lines into font categories aids transcription because single font Optical Character Recognition (OCR) is generally more accurate than omni-font OCR. We pr…
Document Image Binarization with Fully Convolutional Neural Networks
Chris Tensmeyer, Tony Martinez
Binarization of degraded historical manuscript images is an important pre-processing step for many document processing tasks. We formulate binarization as a pixel classification le…