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 51100 of 158 papers

TitleStatusHype
What Makes for Good Visual Tokenizers for Large Language Models?Code1
Heatmap-based Object Detection and Tracking with a Fully Convolutional Neural NetworkCode1
Few-shot Object Counting with Similarity-Aware Feature EnhancementCode1
Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-CaseCode1
IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance SamplingCode1
VLCounter: Text-aware Visual Representation for Zero-Shot Object CountingCode1
RGB-D Indiscernible Object Counting in Underwater ScenesCode1
Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic CountingCode1
Unsupervised Domain Adaptation For Plant Organ CountingCode1
Training-free Object Counting with PromptsCode1
Zero-shot Object CountingCode1
Automating cell counting in fluorescent microscopy through deep learning with c-ResUnetCode1
TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question AnsweringCode1
Car Object Counting and Position Estimation via Extension of the CLIP-EBC FrameworkCode0
AFreeCA: Annotation-Free Counting for AllCode0
A Unified Object Counting Network with Object Occupation PriorCode0
Class-Agnostic CountingCode0
Counting Everyday Objects in Everyday ScenesCode0
Dense Center-Direction Regression for Object Counting and Localization with Point SupervisionCode0
Domain Randomization for Object CountingCode0
GCA-SUNet: A Gated Context-Aware Swin-UNet for Exemplar-Free CountingCode0
Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-ReferringCode0
Improving Contrastive Learning for Referring Expression CountingCode0
Improving Object Counting with Heatmap RegulationCode0
Learning Spatial Similarity Distribution for Few-shot Object CountingCode0
Object Counting and Instance Segmentation with Image-level SupervisionCode0
MoVie: Revisiting Modulated Convolutions for Visual Counting and BeyondCode0
TallyQA: Answering Complex Counting QuestionsCode0
Towards Partial Supervision for Generic Object Counting in Natural ScenesCode0
Towards perspective-free object counting with deep learningCode0
Vision Transformers for Weakly-Supervised Microorganism EnumerationCode0
Where are the Blobs: Counting by Localization with Point SupervisionCode0
Learning-to-Count by Learning-to-Rank: Weakly Supervised Object Counting & Localization Using Only Pairwise Image Rankings0
Fast-moving object counting with an event camera0
Learning to Count Grave Sites for Cemetery Observation Models With Satellite Imagery0
Learning To Count Objects in Images0
Learning to Count Objects with Few Exemplar Annotations0
Learning What NOT to Count0
Low-Power Object Counting with Hierarchical Neural Networks0
Mamba-MOC: A Multicategory Remote Object Counting via State Space Model0
Marmot: Multi-Agent Reasoning for Multi-Object Self-Correcting in Improving Image-Text Alignment0
MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams0
Expanding Zero-Shot Object Counting with Rich Prompts0
Mutually-Aware Feature Learning for Few-Shot Object Counting0
Shifted Autoencoders for Point Annotation Restoration in Object Counting0
Enhancing Zero-shot Counting via Language-guided Exemplar Learning0
Zero-Shot Object Counting with Language-Vision Models0
Object counting from aerial remote sensing images: application to wildlife and marine mammals0
Global Sum Pooling: A Generalization Trick for Object Counting with Small Datasets of Large Images0
Object Counting: You Only Need to Look at One0
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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