5 citations · 12 across the 5 of their papers we have counts for
6 papers
CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentation
Leon Sick, Dominik Engel, Sebastian Hartwig +2
Traditionally, algorithms that learn to segment object instances in 2D images have heavily relied on large amounts of human-annotated data. Only recently, novel approaches have eme…
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…
HPSCAN: Human Perception-Based Scattered Data Clustering
Sebastian Hartwig, Christian van Onzenoodt, Dominik Engel +2
Cluster separation is a task typically tackled by widely used clustering techniques, such as k-means or DBSCAN. However, these algorithms are based on non-perceptual metrics, and o…
AutoTherm: A Dataset and Benchmark for Thermal Comfort Estimation Indoors and in Vehicles
Mark Colley, Sebastian Hartwig, Albin Zeqiri +2
Thermal comfort inside buildings is a well-studied field where human judgment for thermal comfort is collected and may be used for automatic thermal comfort estimation. However, in…
Monocular Depth Decomposition of Semi-Transparent Volume Renderings
Dominik Engel, Sebastian Hartwig, Timo Ropinski
Neural networks have shown great success in extracting geometric information from color images. Especially, monocular depth estimation networks are increasingly reliable in real-wo…
Training Object Detectors on Synthetic Images Containing Reflecting Materials
Sebastian Hartwig, Timo Ropinski
One of the grand challenges of deep learning is the requirement to obtain large labeled training data sets. While synthesized data sets can be used to overcome this challenge, it i…