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 …

Chart images are commonly used for data visualization. Automatically reading the chart
values is a key step for chart content understanding. Charts have a lot of variations in style …

Charts are a powerful tool for visually conveying complex data, but their comprehension
poses a challenge due to the diverse chart types and intricate components. Existing chart …

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 …

Automatic data extraction from charts is challenging for two reasons: there exist many
relations among objects in a chart, which is not a common consideration in general …

Visual chart recognition systems are gaining increasing attention due to the growing
demand for automatically identifying table headers and values from chart images. Current …

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 commonly used as a graphical representation for visualizing numerical data in
digital documents. For many legacy charts or scientific charts, however, underlying data is …

Chart parsing poses a significant challenge due to the diversity of styles, values, texts, and
so forth. Even advanced large vision-language models (LVLMs) with billions of parameters …

Data visualization in the form of charts plays a pivotal role in data analysis, offering critical
insights and aiding in informed decision-making. Automatic chart understanding has …