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 121–130 of 318 papers

Title	Date	Tasks	Status	Score
SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation	Nov 30, 2022	Graph GenerationImage Generation	CodeCode Available	5
Scene Graph Generation from Objects, Phrases and Region Captions	Jul 31, 2017	Graph Generationobject-detection	CodeCode Available	5
DSGG: Dense Relation Transformer for an End-to-end Scene Graph Generation	Mar 21, 2024	Graph GenerationGraph Matching	CodeCode Available	5
S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in OR	Feb 22, 2024	Graph Generationobject-detection	CodeCode Available	5
ReFormer: The Relational Transformer for Image Captioning	Jul 29, 2021	Graph GenerationImage Captioning	CodeCode Available	5
Head-Tail Cooperative Learning Network for Unbiased Scene Graph Generation	Aug 23, 2023	Graph GenerationPrediction	CodeCode Available	5
Haystack: A Panoptic Scene Graph Dataset to Evaluate Rare Predicate Classes	Sep 5, 2023	Graph GenerationScene Graph Generation	CodeCode Available	5
Adaptive Visual Scene Understanding: Incremental Scene Graph Generation	Oct 2, 2023	BenchmarkingContinual Learning	CodeCode Available	5
Taking A Closer Look at Visual Relation: Unbiased Video Scene Graph Generation with Decoupled Label Learning	Mar 23, 2023	Graph GenerationRelation Prediction	CodeCode Available	5
GPT4SGG: Synthesizing Scene Graphs from Holistic and Region-specific Narratives	Dec 7, 2023	Graph GenerationLanguage Modelling	CodeCode Available	5

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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