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

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Showing 101–125 of 158 papers

Title	Date	Tasks	Status
OmniCount: Multi-label Object Counting with Semantic-Geometric Priors	Mar 8, 2024	ObjectObject Counting	—Unverified
Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts	Dec 1, 2023	Chart Question AnsweringDocument AI	—Unverified
OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models	Jun 3, 2025	Object CountingSpatial Reasoning	—Unverified
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications	Dec 23, 2023	geo-localizationimage-classification	—Unverified
Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark	Nov 20, 2024	Object CountingOptical Flow Estimation	—Unverified
Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models	May 5, 2024	Object Counting	—Unverified
People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting	Nov 15, 2017	Cultural Vocal Bursts Intensity PredictionObject	—Unverified
Tolerating Annotation Displacement in Dense Object Counting via Point Annotation Probability Map	Jul 29, 2023	Object Countingregression	—Unverified
Effectiveness Assessment of Recent Large Vision-Language Models	Mar 7, 2024	Anomaly DetectionAttribute	—Unverified
Dynamic Conditional Networks for Few-Shot Learning	Sep 1, 2018	Face GenerationFew-Shot Learning	—Unverified
Drone-based Object Counting by Spatially Regularized Regional Proposal Network	Jul 19, 2017	Object CountingRegion Proposal	—Unverified
Real-Time Object Detection in Occluded Environment with Background Cluttering Effects Using Deep Learning	Jan 2, 2024	Data AugmentationObject Counting	—Unverified
Do Object Detection Localization Errors Affect Human Performance and Trust?	Jan 31, 2024	ObjectObject Counting	—Unverified
Distortion-Adaptive Grape Bunch Counting for Omnidirectional Images	Aug 28, 2020	Data AugmentationObject Counting	—Unverified
Dilated-Scale-Aware Attention ConvNet For Multi-Class Object Counting	Dec 15, 2020	ObjectObject Counting	—Unverified
Diffusion-based Data Augmentation for Object Counting Problems	Jan 25, 2024	Crowd CountingData Augmentation	—Unverified
Reverse Perspective Network for Perspective-Aware Object Counting	Jun 1, 2020	ObjectObject Counting	—Unverified
Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding	Feb 17, 2025	Arithmetic ReasoningChart Understanding	—Unverified
Density Map Distillation for Incremental Object Counting	Apr 11, 2023	Exemplar-FreeIncremental Learning	—Unverified
DeepSetNet: Predicting Sets with Deep Neural Networks	Nov 28, 2016	image-classificationImage Classification	—Unverified
RSVQA: Visual Question Answering for Remote Sensing Data	Mar 16, 2020	Land Cover ClassificationObject Counting	—Unverified
Deep-Learning-based Counting Methods, Datasets, and Applications in Agriculture -- A Review	Mar 5, 2023	Deep LearningObject Counting	—Unverified
Counting the uncountable: deep semantic density estimation from Space	Sep 19, 2018	Density EstimationObject	—Unverified
Segmentação e contagem de troncos de madeira utilizando deep learning e processamento de imagens	Aug 31, 2023	Object CountingSegmentation	—Unverified
Counting Stacked Objects from Multi-View Images	Nov 28, 2024	3D geometryObject Counting	—Unverified

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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