Scene Graph Detection
7 papers with code • 3 benchmarks • 4 datasets
Latest papers
Enhancing Scene Graph Generation with Hierarchical Relationships and Commonsense Knowledge
This work presents an enhanced approach to generating scene graphs by incorporating a relationship hierarchy and commonsense knowledge.
NeuSyRE: Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph Enrichment
We present a loosely-coupled neuro-symbolic visual understanding and reasoning framework that employs a DNN-based pipeline for object detection and multi-modal pairwise relationship prediction for scene graph generation and leverages common sense knowledge in heterogenous knowledge graphs to enrich scene graphs for improved downstream reasoning.
Expressive Scene Graph Generation Using Commonsense Knowledge Infusion for Visual Understanding and Reasoning
These results depict the effectiveness of commonsense knowledge infusion in improving the performance and expressiveness of scene graph generation for visual understanding and reasoning tasks.
Fine-Grained Scene Graph Generation with Data Transfer
Scene graph generation (SGG) is designed to extract (subject, predicate, object) triplets in images.
Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
Dynamic scene graph generation from a video is challenging due to the temporal dynamics of the scene and the inherent temporal fluctuations of predictions.
Recovering the Unbiased Scene Graphs from the Biased Ones
Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects.
Energy-Based Learning for Scene Graph Generation
The proposed formulation allows for efficiently incorporating the structure of scene graphs in the output space.