5 citations · 5 across the 5 of their papers we have counts for
5 papers
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…
Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images
Hannah Kniesel, Leon Sick, Tristan Payer +5
Current state-of-the-art methods for object detection rely on annotated bounding boxes of large data sets for training. However, obtaining such annotations is expensive and can req…
Active Learning Inspired ControlNet Guidance for Augmenting Semantic Segmentation Datasets
Hannah Kniesel, Pedro Hermosilla, Timo Ropinski
Recent advances in conditional image generation from diffusion models have shown great potential in achieving impressive image quality while preserving the constraints introduced b…
A Survey on Quality Metrics for Text-to-Image Generation
Sebastian Hartwig, Dominik Engel, Leon Sick +6
AI-based text-to-image models do not only excel at generating realistic images, they also give designers more and more fine-grained control over the image content. Consequently, th…
Clean Implicit 3D Structure from Noisy 2D STEM Images
Hannah Kniesel, Timo Ropinski, Tim Bergner +5
Scanning Transmission Electron Microscopes (STEMs) acquire 2D images of a 3D sample on the scale of individual cell components. Unfortunately, these 2D images can be too noisy to b…