139 citations · 193 across the 5 of their papers we have counts for
6 papers
MolGrapher: Graph-based Visual Recognition of Chemical Structures
Lucas Morin, Martin Danelljan, Maria Isabel Agea +5
The automatic analysis of chemical literature has immense potential to accelerate the discovery of new materials and drugs. Much of the critical information in patent documents and…
ICDAR 2023 Competition on Robust Layout Segmentation in Corporate Documents
Christoph Auer, Ahmed Nassar, Maksym Lysak +3
Transforming documents into machine-processable representations is a challenging task due to their complex structures and variability in formats. Recovering the layout structure an…
DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis
Birgit Pfitzmann, Christoph Auer, Michele Dolfi +2
Accurate document layout analysis is a key requirement for high-quality PDF document conversion. With the recent availability of public, large ground-truth datasets such as PubLayN…
TableFormer: Table Structure Understanding with Transformers
Ahmed Nassar, Nikolaos Livathinos, Maksym Lysak +1
Tables organize valuable content in a concise and compact representation. This content is extremely valuable for systems such as search engines, Knowledge Graph's, etc, since they…
GeoGraph: Learning graph-based multi-view object detection with geometric cues end-to-end
Ahmed Samy Nassar, Stefano D'Aronco, Sébastien Lefèvre +1
In this paper we propose an end-to-end learnable approach that detects static urban objects from multiple views, re-identifies instances, and finally assigns a geographic position…
Simultaneous multi-view instance detection with learned geometric soft-constraints
Ahmed Samy Nassar, Sebastien Lefevre, Jan D. Wegner
We propose to jointly learn multi-view geometry and warping between views of the same object instances for robust cross-view object detection. What makes multi-view object instance…