SOTAVerified

Scene Graph Generation

A scene graph is a structured representation of an image, where nodes in a scene graph correspond to object bounding boxes with their object categories, and edges correspond to their pairwise relationships between objects. The task of Scene Graph Generation is to generate a visually-grounded scene graph that most accurately correlates with an image.

Source: Scene Graph Generation by Iterative Message Passing

Papers

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Showing 151–200 of 318 papers

TitleStatusHype
Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation—0
Hybrid Reciprocal Transformer with Triplet Feature Alignment for Scene Graph Generation—0
Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation—0
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation—0
Hyper-relationship Learning Network for Scene Graph Generation—0
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
IS-GGT: Iterative Scene Graph Generation With Generative Transformers—0
Iterative Scene Graph Generation—0
Iterative Scene Graph Generation with Generative Transformers—0
Joint Generative Modeling of Scene Graphs and Images via Diffusion Models—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
Label Semantic Knowledge Distillation for Unbiased Scene Graph Generation—0
SPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning—0
Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scene—0
Unconditional Scene Graph Generation—0
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation—0
Learning of Visual Relations: The Devil is in the Tails—0
Understanding the Role of Scene Graphs in Visual Question Answering—0
Learning Structured Representations of Visual Scenes—0
Attentive Relational Networks for Mapping Images to Scene Graphs—0
Learning To Generate Scene Graph from Head to Tail—0
SrTR: Self-reasoning Transformer with Visual-linguistic Knowledge for Scene Graph Generation—0
Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation—0
STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation—0
Leveraging Auxiliary Text for Deep Recognition of Unseen Visual Relationships—0
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation—0
Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
Local-Global Information Interaction Debiasing for Dynamic Scene Graph Generation—0
Universal Scene Graph Generation—0
Logical Bias Learning for Object Relation Prediction—0
Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models—0
Mapping High-level Semantic Regions in Indoor Environments without Object Recognition—0
Meta Spatio-Temporal Debiasing for Video Scene Graph Generation—0
Assisting Scene Graph Generation with Self-Supervision—0
Motion-aware Contrastive Learning for Temporal Panoptic Scene Graph Generation—0
Navigating the Unseen: Zero-shot Scene Graph Generation via Capsule-Based Equivariant Features—0
Neural Belief Propagation for Scene Graph Generation—0
Neuro-Symbolic Scene Graph Conditioning for Synthetic Image Dataset Generation—0
Neuro-Symbolic Visual Reasoning: Disentangling "Visual" from "Reasoning"—0
NICEST: Noisy Label Correction and Training for Robust Scene Graph Generation—0
Visual Semantic Information Pursuit: A Survey—0
Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation—0
NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving—0
TD^2-Net: Toward Denoising and Debiasing for Dynamic Scene Graph Generation—0
On Certified Generalization in Structured Prediction—0
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All datasetsVisual Genome4D-OR3R-ScanVRDGQAMM-ORMS-COCO

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ExpressiveSGGR@10039.12—Unverified
2NeuSyRER@10039.1—Unverified
3KnowZRelzR@10035.65—Unverified
4SpeaQ (without reweighting)Recall@5032.9—Unverified
5SpeaQ (with reweighting)Recall@5032.1—Unverified
6Causal-TDERecall@5031.93—Unverified
7SG-EBMRecall@5031.74—Unverified
8GPS-NetRecall@5028.9—Unverified
9LOGINRecall@5028.2—Unverified
10VCTreeRecall@5027.9—Unverified
#ModelMetricClaimedVerifiedStatus
1ORacleF10.91—Unverified
2MM2SGF10.9—Unverified
3Pix2SGF10.9—Unverified
4LABRAD-ORF10.88—Unverified
54D-OR baselineF10.75—Unverified
#ModelMetricClaimedVerifiedStatus
1SceneGraphFusionTop-5 Accuracy0.87—Unverified
23DSSG [Wald2020_3dssg]Top-5 Accuracy0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1FactorizableNetRecall@5018.32—Unverified
2VRDRecall@5018.16—Unverified
#ModelMetricClaimedVerifiedStatus
1KnowZRelzR@10029.56—Unverified
#ModelMetricClaimedVerifiedStatus
1MM2SGMacro F10.53—Unverified
#ModelMetricClaimedVerifiedStatus
1NeuSyRER@10038.5—Unverified