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 5175 of 158 papers

TitleStatusHype
Real-Time Object Detection in Occluded Environment with Background Cluttering Effects Using Deep Learning0
Point Segment and Count: A Generalized Framework for Object CountingCode2
VLCounter: Text-aware Visual Representation for Zero-Shot Object CountingCode1
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications0
EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question AnsweringCode1
Shifted Autoencoders for Point Annotation Restoration in Object Counting0
Visual Program Distillation: Distilling Tools and Programmatic Reasoning into Vision-Language Models0
Omni-SMoLA: Boosting Generalist Multimodal Models with Soft Mixture of Low-rank Experts0
T-Rex: Counting by Visual Prompting0
Point, Segment and Count: A Generalized Framework for Object CountingCode1
Semantic Generative Augmentations for Few-Shot CountingCode1
Zero-Shot Object Counting with Language-Vision Models0
Interactive Class-Agnostic Object Counting0
Segmentação e contagem de troncos de madeira utilizando deep learning e processamento de imagens0
STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance LearningCode1
Tolerating Annotation Displacement in Dense Object Counting via Point Annotation Probability Map0
Learning to Count without AnnotationsCode1
Learning from Pseudo-labeled Segmentation for Multi-Class Object Counting0
Training-free Object Counting with PromptsCode1
RemoteCLIP: A Vision Language Foundation Model for Remote SensingCode2
Object counting from aerial remote sensing images: application to wildlife and marine mammals0
Open-world Text-specified Object CountingCode1
What Makes for Good Visual Tokenizers for Large Language Models?Code1
CLIP-Count: Towards Text-Guided Zero-Shot Object CountingCode1
Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic CountingCode1
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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
6Supervised Density Mapm-reIRMSE-nz0.61Unverified
7LC-ResFCNm-reIRMSE-nz0.61Unverified
8OmnicountmRMSE0Unverified
#ModelMetricClaimedVerifiedStatus
1Aso-sub-ft-3x3m-reIRMSE0.24Unverified
2glance-ft-2Lm-reIRMSE0.23Unverified
3Fast-RCNNm-reIRMSE0.2Unverified
4LC-ResFCNm-reIRMSE0.19Unverified
5Seq-sub-ft-3x3m-reIRMSE0.18Unverified
6Supervised Density Mapm-reIRMSE0.18Unverified
7ensm-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