339 citations
- University of PotsdamDE102 papers
- Karlsruhe Institute of TechnologyDE9 papers
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- École PolytechniqueFR6 papers
- Humboldt-Universität zu BerlinDE6 papers
- Icahn School of Medicine at Mount SinaiUS5 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR5 papers
- The University of AdelaideAU5 papers
- University of TwenteNL5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
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8 papers · 1 filter
KARAMEL: Knowledge-Aware Ranking for Multimodal Entity Linking in the Arts via Heterogeneous Graphs
Raffaele Scaringi, Alejandro Sierra-Múnera, Gennaro Vessio +2
Discovering and disambiguating entities from multimodal and heterogeneous data is a key challenge in discovery science, where relevant knowledge is often implicit and distributed a…
MINGLE: VLMs for Semantically Complex Region Detection in Urban Scenes
Liu Liu, Alexandra Kudaeva, Marco Cipriano +4
Understanding group-level social interactions in public spaces is crucial for urban planning, informing the design of socially vibrant and inclusive environments. Detecting such in…
DocLangID: Improving Few-Shot Training to Identify the Language of Historical Documents
Furkan Simsek, Brian Pfitzmann, Hendrik Raetz +3
Language identification describes the task of recognizing the language of written text in documents. This information is crucial because it can be used to support the analysis of a…
Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation
Josafat-Mattias Burmeister, Marcel Fernandez Rosas, Johannes Hagemann +5
Since labeling medical image data is a costly and labor-intensive process, active learning has gained much popularity in the medical image segmentation domain in recent years. A va…
Synthesis in Style: Semantic Segmentation of Historical Documents using Synthetic Data
Christian Bartz, Hendrik Raetz, Jona Otholt +2
One of the most pressing problems in the automated analysis of historical documents is the availability of annotated training data. The problem is that labeling samples is a time-c…
LoANs: Weakly Supervised Object Detection with Localizer Assessor Networks
Christian Bartz, Haojin Yang, Joseph Bethge +1
Recently, deep neural networks have achieved remarkable performance on the task of object detection and recognition. The reason for this success is mainly grounded in the availabil…