most citedToo Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco

10 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.HC2023

Draco 2: An Extensible Platform to Model Visualization Design

Junran Yang, Péter Ferenc Gyarmati, Zehua Zeng +1

Draco introduced a constraint-based framework to model visualization design in an extensible and testable form. It provides a way to abstract design guidelines from theoretical and…

cs.HC2023★ 10 cited

Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco

Zehua Zeng, Junran Yang, Dominik Moritz +2

Findings from graphical perception can guide visualization recommendation algorithms in identifying effective visualization designs. However, existing algorithms use knowledge from…

cs.CV2023★ 1 cited

Real-time Multi-Object Tracking Based on Bi-directional Matching

Huilan Luo, Zehua Zeng

In recent years, anchor-free object detection models combined with matching algorithms are used to achieve real-time muti-object tracking and also ensure high tracking accuracy. Ho…

cs.HC2021★ 4 cited

An Evaluation-Focused Framework for Visualization Recommendation Algorithms

Zehua Zeng, Phoebe Moh, Fan Du +5

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which a…

cs.HC2021

A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation

Zehua Zeng, Leilani Battle

Selecting appropriate visual encodings is critical to designing effective visualization recommendation systems, yet few findings from graphical perception are typically applied wit…