Research map / Graph learning / Knowledge and temporal graphs
Neural Motifs: Scene Graph Parsing With Global Context
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use object-pair relation frequencies and restrict candidate pairs to overlapping boxes | Freq+Overlap · Visual Genome | mean recall: 39.3 -> 40.7 | Helped |
| Add global contextualized object and edge representations (ablation) | MotifNet · Visual Genome | mean recall: 42.4 -> 43.6 | Helped |
| Replace left-to-right region ordering with confidence-based ordering (ablation) | MotifNet · Visual Genome | mean recall: 43.6 -> 43.5 | No clear effect |
| Replace left-to-right region ordering with descending-size ordering (ablation) | MotifNet · Visual Genome | mean recall: 43.6 -> 43.3 | No clear effect |
| Replace left-to-right region ordering with random ordering (ablation) | MotifNet · Visual Genome | mean recall: 43.6 -> 43.5 | No clear effect |
Closest papers by meaning
- LinkNet: Relational Embedding for Scene Graph (NeurIPS 2018 · similarity 0.90)
- Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction (NeurIPS 2018 · similarity 0.89)
- Scene Graph Generation by Iterative Message Passing (CVPR 2017 · similarity 0.89)
- DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation (CVPR 2024 · similarity 0.87)
- The Underappreciated Power of Vision Models for Graph Structural Understanding (NeurIPS 2025 · similarity 0.86)
- Homomorphism Counts for Graph Neural Networks: All About That Basis (ICML 2024 · similarity 0.86)
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