mlsanityData to 7 Oct 2026

Learning To Count Everything

arXiv 2104.08391 ↗First posted 16 Apr 2021cs.CVcited by 149

Not on the map. Why?

Cited by 20 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Existing works on visual counting primarily focus on one specific category at a time, such as people, animals, and cells. In this paper, we are interested in counting everything, that is to count objects from any category given only a few annotated instances from that category. To this end, we pose counting as a few-shot regression task. To tackle this task, we present a novel method that takes a query image together with a few exemplar objects from the query image and predicts a density map for the presence of all objects of interest in the query image. We also present a novel adaptation strategy to adapt our network to any novel visual category at test time, using only a few exemplar objects from the novel category. We also introduce a dataset of 147 object categories containing over 6000 images that are suitable for the few-shot counting task. The images are annotated with two types of annotation, dots and bounding boxes, and they can be used for developing few-shot counting models. Experiments on this dataset shows that our method outperforms several state-of-the-art object detectors and few-shot counting approaches. Our code and dataset can be found at https://github.com/cvlab-stonybrook/LearningToCountEverything.

Key facts. Cited by 149 papers in the map (data through 7 Oct 2026). Builds on 32 of its 55 references that are in the map. First posted on arXiv 16 Apr 2021.

Builds on

32 of 55 references.

References · 32

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  4. 2017Mask R-CNNcited by 7,259
  5. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  6. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  7. 2016Matching Networks for One Shot Learningcited by 2,246
  8. 2018Fast Online Object Tracking and Segmentation: A Unifying Approachcited by 272
  9. 2018CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenescited by 267
  10. 2018Few-shot Object Detection via Feature Reweightingcited by 265
  11. 2019Few-Shot Object Detection with Attention-RPN and Multi-Relation Detectorcited by 206
  12. 2018Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowdscited by 186
20 more
  1. 2019Bayesian Loss for Crowd Count Estimation with Point Supervisioncited by 162
  2. 2017Drone-based Object Counting by Spatially Regularized Regional Proposal Networkcited by 155
  3. 2020NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localizationcited by 151
  4. 2018Context-Aware Crowd Countingcited by 150
  5. 2019Learning from Synthetic Data for Crowd Counting in the Wildcited by 148
  6. 2020Distribution Matching for Crowd Countingcited by 143
  7. 2020JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Methodcited by 109
  8. 2017Switching Convolutional Neural Network for Crowd Countingcited by 93
  9. 2019Generalized Inner Loop Meta-Learningcited by 92
  10. 2017End-to-end representation learning for Correlation Filter based trackingcited by 90
  11. 2016A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learningcited by 86
  12. 2018Class-Agnostic Countingcited by 85
  13. 2020Localization in the Crowd with Topological Constraintscited by 68
  14. 2016One-shot Learning with Memory-Augmented Neural Networkscited by 60
  15. 2018Leveraging Unlabeled Data for Crowd Counting by Learning to Rankcited by 57
  16. 2018Revisiting Perspective Information for Efficient Crowd Countingcited by 49
  17. 2018Iterative Crowd Countingcited by 48
  18. 2018Divide and Grow: Capturing Huge Diversity in Crowd Images with Incrementally Growing CNNcited by 19
  19. 2020Uncertainty Estimation and Sample Selection for Crowd Countingcited by 11
  20. 2019Crowd Transformer Networkcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 11; 2023: 23; 2024: 35; 2025: 41; 2026: 38.

149 papers.

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  1. 2023LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmarkcited by 169
  2. 2024T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergycited by 94
  3. 2024DINO-X: A Unified Vision Model for Open-World Object Detection and Understandingcited by 85
  4. 2023CLIP-Count: Towards Text-Guided Zero-Shot Object Countingcited by 82
  5. 2022Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Countingcited by 80
  6. 2022CounTR: Transformer-based Generalised Visual Countingcited by 79
  7. 2025Detect Anything via Next Point Predictioncited by 66
  8. 2022A Low-Shot Object Counting Network With Iterative Prototype Adaptationcited by 65
  9. 2023A Comprehensive Survey on Segment Anything Model for Vision and Beyondcited by 64
  10. 2022Few-shot Object Counting with Similarity-Aware Feature Enhancementcited by 62
  11. 2024CountGD: Multi-Modal Open-World Countingcited by 59
  12. 2023Zero-shot Object Countingcited by 57
38 more
  1. 2022Few-shot Object Counting and Detectioncited by 55
  2. 2024DAVE -- A Detect-and-Verify Paradigm for Low-Shot Countingcited by 49
  3. 2023VLCounter: Text-aware Visual Representation for Zero-Shot Object Countingcited by 45
  4. 2022Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervisioncited by 41
  5. 2023Open-world Text-specified Object Countingcited by 41
  6. 2023Point, Segment and Count: A Generalized Framework for Object Countingcited by 39
  7. 2024Assessment of Multimodal Large Language Models in Alignment with Human Valuescited by 36
  8. 2023Training-free Object Counting with Promptscited by 34
  9. 2022Exemplar Free Class Agnostic Countingcited by 32
  10. 2024Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referringcited by 29
  11. 2024UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarioscited by 28
  12. 2023Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Countingcited by 25
  13. 2024Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Modelscited by 24
  14. 2024Zero-shot Object Counting with Good Exemplarscited by 21
  15. 2024A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentationcited by 21
  16. 2023T-Rex: Counting by Visual Promptingcited by 20
  17. 2024LVLM-COUNT: Enhancing the Counting Ability of Large Vision-Language Modelscited by 20
  18. 2026LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decodingcited by 20
  19. 2025T2ICount: Enhancing Cross-modal Understanding for Zero-Shot Countingcited by 19
  20. 2023Can SAM Count Anything? An Empirical Study on SAM Countingcited by 18
  21. 2025Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMscited by 18
  22. 2024OmniCount: Multi-label Object Counting with Semantic-Geometric Priorscited by 16
  23. 2022Interactive Multi-Class Tiny-Object Detectioncited by 14
  24. 2021Object Counting: You Only Need to Look at Onecited by 13
  25. 2023ABC Easy as 123: A Blind Counter for Exemplar-Free Multi-Class Class-agnostic Countingcited by 13
  26. 2024AFreeCA: Annotation-Free Counting for Allcited by 12
  27. 2024Mind the Prompt: A Novel Benchmark for Prompt-based Class-Agnostic Countingcited by 11
  28. 2025Open-World Object Counting in Videoscited by 11
  29. 2024A Fixed-Point Approach to Unified Prompt-Based Countingcited by 10
  30. 2024OVR: A Dataset for Open Vocabulary Temporal Repetition Counting in Videoscited by 10
  31. 2025Exploring Contextual Attribute Density in Referring Expression Countingcited by 10
  32. 2025YOLO-Count: Differentiable Object Counting for Text-to-Image Generationcited by 10
  33. 2023Zero-Shot Object Counting with Language-Vision Modelscited by 9
  34. 2023Interactive Class-Agnostic Object Countingcited by 8
  35. 2024Counting Stacked Objectscited by 8
  36. 2025InstructSAM: A Training-Free Framework for Instruction-Oriented Remote Sensing Object Recognitioncited by 8
  37. 2025CountGD++: Generalized Prompting for Open-World Countingcited by 8
  38. 2025A Survey on Class-Agnostic Counting: Advancements from Reference-Based to Open-World Text-Guided Approachescited by 7

50 most cited of 149 All 149 (JSON)