3 papers
cs.CV2026
Bar-JEPA: Extracting Values from Bar Chart with Joint-Embedding Predictive Architecture
Poonam Poonam, Alexander Epple, Timo Ropinski
Bar charts are commonly used in data visualization, and while they are easily understood by humans, it is non-trivial to extract the underlying data computationally. For a machine-…
cs.CV2026
PaCoNet: Deep Data Extraction for Parallel Coordinates
Poonam Poonam, Hannah Kniesel, Pere-Pau Vázquez +1
Extracting data from visualizations has long challenged computer vision, with current research focused on bar, line, and pie charts, among other low-dimensional visualizations. How…
cs.CV2026
Evaluating Graphical Perception Capabilities of Vision Transformers
Poonam Poonam, Pere-Pau Vázquez, Timo Ropinski
Vision Transformers, ViTs, have emerged as a powerful alternative to convolutional neural networks, CNNs, in a variety of image-based tasks. While CNNs have previously been evaluat…