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Titel:

Relationformer: A Unified Framework for Image-to-Graph Generation

Dokumenttyp:
Proceedings Paper
Autor(en):
Shit, Suprosanna; Koner, Rajat; Wittmann, Bastian; Paetzold, Johannes; Ezhov, Ivan; Li, Hongwei; Pan, Jiazhen; Sharifzadeh, Sahand; Kaissis, Georgios; Tresp, Volker; Menze, Bjoern
Abstract:
A comprehensive representation of an image requires understanding objects and their mutual relationship, especially in image-to-graph generation, e.g., road network extraction, blood-vessel network extraction, or scene graph generation. Traditionally, image-to-graph generation is addressed with a two-stage approach consisting of object detection followed by a separate relation prediction, which prevents simultaneous object-relation interaction. This work proposes a unified one-stage transformer-...     »
Zeitschriftentitel:
Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv
Jahr:
2022
Band / Volume:
13697
Seitenangaben Beitrag:
422-439
Volltext / DOI:
doi:10.1007/978-3-031-19836-6_24
Print-ISSN:
0302-9743
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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