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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 81–90 of 318 papers

Title	Date	Tasks	Status	Hype
Groupwise Query Specialization and Quality-Aware Multi-Assignment for Transformer-based Visual Relationship Detection	Mar 26, 2024	RelationRelationship Detection	CodeCode Available	1
R3CD: Scene Graph to Image Generation with Relation-aware Compositional Contrastive Control Diffusion	Mar 24, 2024	DenoisingImage Generation	—Unverified	0
Predicate Debiasing in Vision-Language Models Integration for Scene Graph Generation Enhancement	Mar 24, 2024	DiversityGraph Generation	—Unverified	0
DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation	Mar 21, 2024	Graph GenerationGraph Matching	CodeCode Available	0
HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation	Mar 18, 2024	Scene Graph Generation	CodeCode Available	2
Mapping High-level Semantic Regions in Indoor Environments without Object Recognition	Mar 11, 2024	Graph GenerationLanguage Modeling	—Unverified	0
Towards Scene Graph Anticipation	Mar 7, 2024	Graph GenerationLong Term Anticipation	CodeCode Available	1
S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in OR	Feb 22, 2024	Graph Generationobject-detection	CodeCode Available	0
Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learning	Jan 26, 2024	Graph GenerationIn-Context Learning	—Unverified	0
SGTR+: End-to-end Scene Graph Generation with Transformer	Jan 23, 2024	graph constructionGraph Generation	CodeCode Available	2

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All datasets Visual Genome 4D-OR 3R-Scan VRD GQA MM-OR MS-COCO

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ExpressiveSGG	R@100	39.12	—	Unverified
2	NeuSyRE	R@100	39.1	—	Unverified
3	KnowZRel	zR@100	35.65	—	Unverified
4	SpeaQ (without reweighting)	Recall@50	32.9	—	Unverified
5	SpeaQ (with reweighting)	Recall@50	32.1	—	Unverified
6	Causal-TDE	Recall@50	31.93	—	Unverified
7	SG-EBM	Recall@50	31.74	—	Unverified
8	GPS-Net	Recall@50	28.9	—	Unverified
9	LOGIN	Recall@50	28.2	—	Unverified
10	VCTree	Recall@50	27.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ORacle	F1	0.91	—	Unverified
2	MM2SG	F1	0.9	—	Unverified
3	Pix2SG	F1	0.9	—	Unverified
4	LABRAD-OR	F1	0.88	—	Unverified
5	4D-OR baseline	F1	0.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SceneGraphFusion	Top-5 Accuracy	0.87	—	Unverified
2	3DSSG [Wald2020_3dssg]	Top-5 Accuracy	0.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FactorizableNet	Recall@50	18.32	—	Unverified
2	VRD	Recall@50	18.16	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	KnowZRel	zR@100	29.56	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MM2SG	Macro F1	0.53	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	NeuSyRE	R@100	38.5	—	Unverified