Object Counting

The goal of Object Counting task is to count the number of object instances in a single image or video sequence. It has many real-world applications such as traffic flow monitoring, crowdedness estimation, and product counting.

Source: Learning to Count Objects with Few Exemplar Annotations

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 76–100 of 158 papers

Title	Date	Tasks	Status	Score
Object Counting and Instance Segmentation with Image-level Supervision	Mar 6, 2019	Image-level Supervised Instance SegmentationInstance Segmentation	CodeCode Available	5
MoVie: Revisiting Modulated Convolutions for Visual Counting and Beyond	Apr 24, 2020	Object CountingQuestion Answering	CodeCode Available	5
TallyQA: Answering Complex Counting Questions	Oct 29, 2018	AttributeObject Counting	CodeCode Available	5
Towards Partial Supervision for Generic Object Counting in Natural Scenes	Dec 13, 2019	image-classificationImage Classification	CodeCode Available	5
Towards perspective-free object counting with deep learning	Jan 1, 2016	Deep LearningObject	CodeCode Available	5
Vision Transformers for Weakly-Supervised Microorganism Enumeration	Dec 3, 2024	Density EstimationInstance Segmentation	CodeCode Available	5
Where are the Blobs: Counting by Localization with Point Supervision	Jul 25, 2018	ObjectObject Counting	CodeCode Available	5
Learning-to-Count by Learning-to-Rank: Weakly Supervised Object Counting & Localization Using Only Pairwise Image Rankings	Sep 29, 2021	Learning-To-RankObject	—Unverified	0
Fast-moving object counting with an event camera	Dec 16, 2022	ObjectObject Counting	—Unverified	0
Learning to Count Grave Sites for Cemetery Observation Models With Satellite Imagery	Sep 22, 2020	Object Counting	—Unverified	0
Learning To Count Objects in Images	Dec 1, 2010	ObjectObject Counting	—Unverified	0
Learning to Count Objects with Few Exemplar Annotations	May 20, 2019	ObjectObject Counting	—Unverified	0
Learning What NOT to Count	Apr 16, 2025	Object CountingZero-Shot Counting	—Unverified	0
Low-Power Object Counting with Hierarchical Neural Networks	Jul 2, 2020	ObjectObject Counting	—Unverified	0
Mamba-MOC: A Multicategory Remote Object Counting via State Space Model	Jan 12, 2025	MambaObject	—Unverified	0
Marmot: Multi-Agent Reasoning for Multi-Object Self-Correcting in Improving Image-Text Alignment	Apr 10, 2025	AI AgentAttribute	—Unverified	0
MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams	Mar 26, 2025	Mathematical ReasoningObject Counting	—Unverified	0
Expanding Zero-Shot Object Counting with Rich Prompts	May 21, 2025	ObjectObject Counting	—Unverified	0
Mutually-Aware Feature Learning for Few-Shot Object Counting	Aug 19, 2024	Object Counting	—Unverified	0
Shifted Autoencoders for Point Annotation Restoration in Object Counting	Dec 12, 2023	General KnowledgeObject	—Unverified	0
Enhancing Zero-shot Counting via Language-guided Exemplar Learning	Feb 8, 2024	Object CountingZero-Shot Counting	—Unverified	0
Zero-Shot Object Counting with Language-Vision Models	Sep 22, 2023	ObjectObject Counting	—Unverified	0
Object counting from aerial remote sensing images: application to wildlife and marine mammals	Jun 17, 2023	Object Counting	—Unverified	0
Global Sum Pooling: A Generalization Trick for Object Counting with Small Datasets of Large Images	May 28, 2018	Crowd CountingObject Counting	—Unverified	0
Object Counting: You Only Need to Look at One	Dec 11, 2021	Feature CorrelationObject	—Unverified	0

Show:10 25 50

← PrevPage 4 of 7Next →

All datasets FSC147 CARPK Pascal VOC 2007 count-test COCO count-test TallyQA-Complex TallyQA-Simple HowMany-QA PASCAL VOC Omnicount-191 TRANCOS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	FamNet	MAE(test)	22.08	—	Unverified
2	Omnicount (Open vocabulary, multi-label, without training)	MAE(test)	18.63	—	Unverified
3	RCC	MAE(test)	17.12	—	Unverified
4	Counting-DETR	MAE(test)	16.79	—	Unverified
5	CounTX (uses text descriptions instead of visual exemplars)	MAE(test)	15.88	—	Unverified
6	LaoNet	MAE(test)	15.78	—	Unverified
7	BMNet+	MAE(test)	14.62	—	Unverified
8	SAFECount	MAE(test)	14.32	—	Unverified
9	GCA-SUN	MAE(test)	14	—	Unverified
10	SPDCN	MAE(test)	13.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOLO (2016)	MAE	156	—	Unverified
2	YOLO9000opt (2017)	MAE	130.4	—	Unverified
3	Faster R-CNN (2015)	MAE	39.88	—	Unverified
4	RetinaNet (2018)	MAE	24.58	—	Unverified
5	LPN Counting (2017)	MAE	22.76	—	Unverified
6	One-Look Regression (2016)	MAE	21.88	—	Unverified
7	RetinaNet (2018)	MAE	16.62	—	Unverified
8	CounTX (uses arbitrary text input to specify object to count, used "the cars" for CARPK)	MAE	8.13	—	Unverified
9	Soft-IoU + EM-Merger unit	MAE	6.77	—	Unverified
10	VLCounter	MAE	6.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Fast-RCNN	m-reIRMSE-nz	0.85	—	Unverified
2	glance-noft-2L	m-reIRMSE-nz	0.73	—	Unverified
3	LC-PSPNet	m-reIRMSE-nz	0.7	—	Unverified
4	Seq-sub-ft-3x3	m-reIRMSE-nz	0.68	—	Unverified
5	ens	m-reIRMSE-nz	0.65	—	Unverified
6	Supervised Density Map	m-reIRMSE-nz	0.61	—	Unverified
7	LC-ResFCN	m-reIRMSE-nz	0.61	—	Unverified
8	Omnicount	mRMSE	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Aso-sub-ft-3x3	m-reIRMSE	0.24	—	Unverified
2	glance-ft-2L	m-reIRMSE	0.23	—	Unverified
3	Fast-RCNN	m-reIRMSE	0.2	—	Unverified
4	LC-ResFCN	m-reIRMSE	0.19	—	Unverified
5	Seq-sub-ft-3x3	m-reIRMSE	0.18	—	Unverified
6	Supervised Density Map	m-reIRMSE	0.18	—	Unverified
7	ens	m-reIRMSE	0.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SMoLA-PaLI-X Specialist	Accuracy	77.1	—	Unverified
2	PaLI-X-VPD	Accuracy	76.6	—	Unverified
3	SMoLA-PaLI-X Generalist (0 shot)	Accuracy	70.7	—	Unverified
4	MoVie-ResNeXt	Accuracy	56.8	—	Unverified
5	RCN	Accuracy	56.2	—	Unverified
6	MoVie	Accuracy	54.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SMoLA-PaLI-X Specialist	Accuracy	86.3	—	Unverified
2	PaLI-X-VPD	Accuracy	86.2	—	Unverified
3	SMoLA-PaLI-X Generalist (0 shot)	Accuracy	83.3	—	Unverified
4	MoVie-ResNeXt	Accuracy	74.9	—	Unverified
5	RCN	Accuracy	71.8	—	Unverified
6	MoVie	Accuracy	70.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MoVie-ResNeXt	Accuracy	64	—	Unverified
2	MoVie	Accuracy	61.2	—	Unverified
3	RCN	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CEOES	mRMSE	0.42	—	Unverified
2	ILC	mRMSE	0.29	—	Unverified
3	TFOC	mRMSE	0.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Omnicount	mRMSE	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GauNet (ResNet-50)	MAE	2.1	—	Unverified