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 176–200 of 318 papers

TitleStatusHype
S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in ORCode0
Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learning—0
TD^2-Net: Toward Denoising and Debiasing for Dynamic Scene Graph Generation—0
Joint Generative Modeling of Scene Graphs and Images via Diffusion Models—0
Contextual Associated Triplet Queries for Panoptic Scene Graph Generation—0
CLIP-Driven Open-Vocabulary 3D Scene Graph Generation via Cross-Modality Contrastive Learning—0
ALF: Adaptive Label Finetuning for Scene Graph Generation—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific NarrativesCode0
HIG: Hierarchical Interlacement Graph Approach to Scene Graph Generation in Video Understanding—0
HAtt-Flow: Hierarchical Attention-Flow Mechanism for Group Activity Scene Graph Generation in Videos—0
Two Stream Scene Understanding on Graph Embedding—0
Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detection—0
Semantic Scene Graph Generation Based on an Edge Dual Scene Graph and Message Passing Neural Network—0
FloCoDe: Unbiased Dynamic Scene Graph Generation with Temporal Consistency and Correlation Debiasing—0
VidCoM: Fast Video Comprehension through Large Language Models with Multimodal Tools—0
TextPSG: Panoptic Scene Graph Generation from Textual Descriptions—0
Domain-wise Invariant Learning for Panoptic Scene Graph Generation—0
Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationCode0
Logical Bias Learning for Object Relation Prediction—0
Predicate Classification Using Optimal Transport Loss in Scene Graph Generation—0
Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention—0
STDG: Semi-Teacher-Student Training Paradigram for Depth-guided One-stage Scene Graph Generation—0
RepSGG: Novel Representations of Entities and Relationships for Scene Graph Generation—0
Haystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate ClassesCode0
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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