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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 318 papers

TitleStatusHype
Weakly Supervised Video Scene Graph Generation via Natural Language SupervisionCode1
Weakly Supervised Visual Semantic ParsingCode1
CogTree: Cognition Tree Loss for Unbiased Scene Graph GenerationCode1
LLaVA-SpaceSGG: Visual Instruct Tuning for Open-vocabulary Scene Graph Generation with Enhanced Spatial RelationsCode1
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph GenerationCode1
HL-Net: Heterophily Learning Network for Scene Graph GenerationCode1
Are scene graphs good enough to improve Image Captioning?Code1
Leveraging Predicate and Triplet Learning for Scene Graph GenerationCode1
Less is More: Toward Zero-Shot Local Scene Graph Generation via Foundation ModelsCode1
One-shot Scene Graph GenerationCode1
Pair then Relation: Pair-Net for Panoptic Scene Graph GenerationCode1
NODIS: Neural Ordinary Differential Scene UnderstandingCode1
Scene Graph Generation with Role-Playing Large Language ModelsCode1
SPAN: Learning Similarity between Scene Graphs and Images with TransformersCode1
Visual Distant Supervision for Scene Graph GenerationCode1
CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning—0
Ensemble Predicate Decoding for Unbiased Scene Graph Generation—0
CAT-SG: A Large Dynamic Scene Graph Dataset for Fine-Grained Understanding of Cataract Surgery—0
Interpretable End-to-End Driving Model for Implicit Scene Understanding—0
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows—0
Informative Scene Graph Generation via Debiasing—0
Enhanced Data Transfer Cooperating with Artificial Triplets for Scene Graph Generation—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
A Reverse Causal Framework to Mitigate Spurious Correlations for Debiasing Scene Graph Generation—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Predicate Debiasing in Vision-Language Models Integration for Scene Graph Generation Enhancement—0
Improving Scene Graph Generation with Superpixel-Based Interaction Learning—0
Importance Weighted Structure Learning for Scene Graph Generation—0
Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks—0
Dynamic Scene Graph Generation via Anticipatory Pre-Training—0
Hyper-relationship Learning Network for Scene Graph Generation—0
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation—0
Context-aware Mixture-of-Experts for Unbiased Scene Graph Generation—0
NICEST: Noisy Label Correction and Training for Robust Scene Graph Generation—0
Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation—0
Hybrid Reciprocal Transformer with Triplet Feature Alignment for Scene Graph Generation—0
Dual ResGCN for Balanced Scene GraphGeneration—0
HOSE-Net: Higher Order Structure Embedded Network for Scene Graph Generation—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—0
Dual Embodied-Symbolic Concept Representations for Deep Learning—0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—0
Approximate Query Matching for Image Retrieval—0
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation—0
Hi-Dyna Graph: Hierarchical Dynamic Scene Graph for Robotic Autonomy in Human-Centric Environments—0
Doubly Reparameterized Importance Weighted Structure Learning for Scene Graph Generation—0
Domain-wise Invariant Learning for Panoptic Scene Graph Generation—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