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 21–30 of 318 papers

Title	Date	Tasks	Status	Hype
ProVision: Programmatically Scaling Vision-centric Instruction Data for Multimodal Language Models	Dec 9, 2024	Graph GenerationScene Graph Generation	CodeCode Available	1
Scene Graph Generation with Role-Playing Large Language Models	Oct 20, 2024	DescriptiveGraph Generation	CodeCode Available	1
Semantic Diversity-aware Prototype-based Learning for Unbiased Scene Graph Generation	Jul 22, 2024	DiversityGraph Generation	CodeCode Available	1
OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal Models	Jul 15, 2024	Graph Generationobject-detection	CodeCode Available	1
A Fair Ranking and New Model for Panoptic Scene Graph Generation	Jul 12, 2024	Graph GenerationPanoptic Scene Graph Generation	CodeCode Available	1
Leveraging Predicate and Triplet Learning for Scene Graph Generation	Jun 4, 2024	Graph GenerationRelation	CodeCode Available	1
OED: Towards One-stage End-to-End Dynamic Scene Graph Generation	May 27, 2024	Graph Generationobject-detection	CodeCode Available	1
A Review and Efficient Implementation of Scene Graph Generation Metrics	Apr 15, 2024	BenchmarkingGraph Generation	CodeCode Available	1
ORacle: Large Vision-Language Models for Knowledge-Guided Holistic OR Domain Modeling	Apr 10, 2024	Data AugmentationGraph Generation	CodeCode Available	1
SportsHHI: A Dataset for Human-Human Interaction Detection in Sports Videos	Apr 6, 2024	Graph GenerationRelation	CodeCode Available	1

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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