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 …

We present a state‐of‐the‐art report on visualization corpora in automated chart analysis
research. We survey 56 papers that created or used a visualization corpus as the input of …

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 …

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 …

Extracting underlying data from rasterized charts is tedious and inaccurate; values might be
partially occluded or hard to distinguish, and the quality of the image limits the precision of …

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

This paper proposes a method for automatically recovering data from chart images. In
particular we focus on the task of estimating line charts, as the most common chart type, in a …

Reverse-engineering bar charts extract textual and numeric information from the visual
representations of bar charts to support application scenarios that require the underlying …

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