[2601.15133] Graph Recognition via Subgraph Prediction

Computer Science > Computer Vision and Pattern Recognition arXiv:2601.15133 (cs) [Submitted on 21 Jan 2026 (v1), last revised 3 Mar 2026 (this version, v2)] Title:Graph Recognition via Subgraph Prediction Authors:André Eberhard, Gerhard Neumann, Pascal Friederich View a PDF of the paper titled Graph Recognition via Subgraph Prediction, by Andr\'e Eberhard and 2 other authors View PDF HTML (experimental) Abstract:Despite tremendous improvements in tasks such as image classification, object detection, and segmentation, the recognition of visual relationships, commonly modeled as the extraction of a graph from an image, remains a challenging task. We believe that this mainly stems from the fact that there is no canonical way to approach the visual graph recognition task. Most existing solutions are specific to a problem and cannot be transferred between different contexts out-of-the box, even though the conceptual problem remains the same. With broad applicability and simplicity in mind, in this paper we develop a method, \textbf{Gra}ph Recognition via \textbf{S}ubgraph \textbf{P}rediction (\textbf{GraSP}), for recognizing graphs in images. We show across several synthetic benchmarks and one real-world application that our method works with a set of diverse types of graphs and their drawings, and can be transferred between tasks without task-specific modifications, paving the way to a more unified framework for visual graph recognition. Subjects: Computer Vision and Pattern R...