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VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis
2022
International Conference on Machine Learning
Scene graphs are powerful abstractions that capture relationships between objects in images by modeling objects as nodes and relationships as edges. Generation of realistic novel scene graphs has applications like scene synthesis and data augmentation for supervised learning. Existing graph generative models are predominantly targeted toward molecular graphs, leveraging the limited vocabulary of atoms and bonds and also the welldefined semantics of chemical compounds. In contrast, scene graphs
dblp:conf/icml/VermaDAVC22
fatcat:v62rconnerepdaq4x7unptyueq