Visualizations themselves have become a data format. Akin to other data formats such as
text and images, visualizations are increasingly created, stored, shared, and (re-) used with …

Abstract Chart Visualizations (CharVis) such as charts/plots and diagrams are commonly
used in documents for representing the underlying quantitative information. However, the …

We investigate how to automatically recover visual encodings from a chart image, primarily
using inferred text elements. We contribute an end‐to‐end pipeline which takes a bitmap …

Charts are useful communication tools for the presentation of data in a visually appealing
format that facilitates comprehension. There have been many studies dedicated to chart …

The advancements of search engines for traditional text documents have enabled the
effective retrieval of massive textual information in a resource-efficient manner. However …

In this paper, we propose a technique for automatically annotating visualizations according
to the textual description. In our approach, visual elements in the target visualization, along …

Visualization designers regularly use color to encode quantitative or categorical data.
However, visualizations “in the wild” often violate perceptual color design principles and …

Data extraction from line-chart images is an essential component of the automated
document understanding process, as line charts are a ubiquitous data visualization format …

Graphs has been a ubiquitous way of representing heterogeneous data. There are many
studies focused on graph learning highlighting the approaches for graph data extraction …

Machine learning specific scholarly full-text documents contain a number of result-figures
expressing valuable data, including experimental results, evaluations, and cross-model …