Scene Graph Classification
7 papers with code • 2 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Scene Graph Classification
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Visual Genome
ImageCLEF-DA
Latest papers
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge
bowen-upenn/scene_graph_commonsense
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This work presents an enhanced approach to generating scene graphs by incorporating a relationship hierarchy and commonsense knowledge.
HL-Net: Heterophily Learning Network for Scene Graph Generation
Despite their effectiveness, however, current SGG methods only assume scene graph homophily while ignoring heterophily.
Fine-Grained Scene Graph Generation with Data Transfer
waxnkw/ietrans-sgg.pytorch
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Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Recovering the Unbiased Scene Graphs from the Biased Ones
coldmanck/recovering-unbiased-scene-graphs
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Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects.
Tackling the Challenges in Scene Graph Generation with Local-to-Global Interactions
sangminwoo/Local-to-Global-Interaction-Networks-SGG
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To quantify how much LOGIN is aware of relational direction, a new diagnostic task called Bidirectional Relationship Classification (BRC) is also proposed.
Energy-Based Learning for Scene Graph Generation
mods333/energy-based-scene-graph
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CVPR 2021
The proposed formulation allows for efficiently incorporating the structure of scene graphs in the output space.
Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
shikorab/SceneGraph
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NeurIPS 2018
Machine understanding of complex images is a key goal of artificial intelligence.
