SOTAVerified

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

Showing 126150 of 158 papers

TitleStatusHype
OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models0
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications0
Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models0
People, Penguins and Petri Dishes: Adapting Object Counting Models To New Visual Domains And Object Types Without Forgetting0
Tolerating Annotation Displacement in Dense Object Counting via Point Annotation Probability Map0
Real-Time Object Detection in Occluded Environment with Background Cluttering Effects Using Deep Learning0
TFCounter:Polishing Gems for Training-Free Object Counting0
Towards Locally Consistent Object Counting with Constrained Multi-stage Convolutional Neural Networks0
T-Rex: Counting by Visual Prompting0
TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection0
Understanding the Ability of Deep Neural Networks to Count Connected Components in Images0
Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models0
Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding0
0-1 phase transitions in sparse spiked matrix estimation0
Towards perspective-free object counting with deep learningCode0
Improving Contrastive Learning for Referring Expression CountingCode0
AFreeCA: Annotation-Free Counting for AllCode0
Class-Agnostic CountingCode0
Car Object Counting and Position Estimation via Extension of the CLIP-EBC FrameworkCode0
Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-ReferringCode0
GCA-SUNet: A Gated Context-Aware Swin-UNet for Exemplar-Free CountingCode0
Domain Randomization for Object CountingCode0
Vision Transformers for Weakly-Supervised Microorganism EnumerationCode0
A Unified Object Counting Network with Object Occupation PriorCode0
Dense Center-Direction Regression for Object Counting and Localization with Point SupervisionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FamNetMAE(test)22.08Unverified
2Omnicount (Open vocabulary, multi-label, without training)MAE(test)18.63Unverified
3RCCMAE(test)17.12Unverified
4Counting-DETRMAE(test)16.79Unverified
5CounTX (uses text descriptions instead of visual exemplars)MAE(test)15.88Unverified
6LaoNetMAE(test)15.78Unverified
7BMNet+MAE(test)14.62Unverified
8SAFECountMAE(test)14.32Unverified
9GCA-SUNMAE(test)14Unverified
10SPDCNMAE(test)13.51Unverified
#ModelMetricClaimedVerifiedStatus
1YOLO (2016)MAE156Unverified
2YOLO9000opt (2017)MAE130.4Unverified
3Faster R-CNN (2015)MAE39.88Unverified
4RetinaNet (2018)MAE24.58Unverified
5LPN Counting (2017)MAE22.76Unverified
6One-Look Regression (2016)MAE21.88Unverified
7RetinaNet (2018)MAE16.62Unverified
8CounTX (uses arbitrary text input to specify object to count, used "the cars" for CARPK)MAE8.13Unverified
9Soft-IoU + EM-Merger unitMAE6.77Unverified
10VLCounterMAE6.46Unverified
#ModelMetricClaimedVerifiedStatus
1Fast-RCNNm-reIRMSE-nz0.85Unverified
2glance-noft-2Lm-reIRMSE-nz0.73Unverified
3LC-PSPNetm-reIRMSE-nz0.7Unverified
4Seq-sub-ft-3x3m-reIRMSE-nz0.68Unverified
5ensm-reIRMSE-nz0.65Unverified
6LC-ResFCNm-reIRMSE-nz0.61Unverified
7Supervised Density Mapm-reIRMSE-nz0.61Unverified
8OmnicountmRMSE0Unverified
#ModelMetricClaimedVerifiedStatus
1Aso-sub-ft-3x3m-reIRMSE0.24Unverified
2glance-ft-2Lm-reIRMSE0.23Unverified
3Fast-RCNNm-reIRMSE0.2Unverified
4LC-ResFCNm-reIRMSE0.19Unverified
5Supervised Density Mapm-reIRMSE0.18Unverified
6ensm-reIRMSE0.18Unverified
7Seq-sub-ft-3x3m-reIRMSE0.18Unverified
#ModelMetricClaimedVerifiedStatus
1SMoLA-PaLI-X SpecialistAccuracy77.1Unverified
2PaLI-X-VPDAccuracy76.6Unverified
3SMoLA-PaLI-X Generalist (0 shot)Accuracy70.7Unverified
4MoVie-ResNeXtAccuracy56.8Unverified
5RCNAccuracy56.2Unverified
6MoVieAccuracy54.1Unverified
#ModelMetricClaimedVerifiedStatus
1SMoLA-PaLI-X SpecialistAccuracy86.3Unverified
2PaLI-X-VPDAccuracy86.2Unverified
3SMoLA-PaLI-X Generalist (0 shot)Accuracy83.3Unverified
4MoVie-ResNeXtAccuracy74.9Unverified
5RCNAccuracy71.8Unverified
6MoVieAccuracy70.8Unverified
#ModelMetricClaimedVerifiedStatus
1MoVie-ResNeXtAccuracy64Unverified
2MoVieAccuracy61.2Unverified
3RCNAccuracy60.3Unverified
#ModelMetricClaimedVerifiedStatus
1CEOESmRMSE0.42Unverified
2ILCmRMSE0.29Unverified
3TFOCmRMSE0.01Unverified
#ModelMetricClaimedVerifiedStatus
1OmnicountmRMSE0Unverified
#ModelMetricClaimedVerifiedStatus
1GauNet (ResNet-50)MAE2.1Unverified