| An Accurate Car Counting in Aerial Images Based on Convolutional Neural Networks | ✓ Link | 2.12 | 3.02 | HLCNN | 2021-07-13 |
| Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework | ✓ Link | 4.01 | 6.02 | CLIP-LOCAR | 2025-07-11 |
| Few-shot Object Counting with Similarity-Aware Feature Enhancement | ✓ Link | 5.33 | 7.04 | SAFECount | 2022-01-22 |
| CounTR: Transformer-based Generalised Visual Counting | ✓ Link | 5.75 | 7.45 | CounTR | 2022-08-29 |
| Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting | ✓ Link | 5.76 | 7.83 | BMNet+ | 2022-03-16 |
| VLCounter: Text-aware Visual Representation for Zero-Shot Object Counting | ✓ Link | 6.46 | 8.68 | VLCounter | 2023-12-27 |
| Precise Detection in Densely Packed Scenes | ✓ Link | 6.77 | 8.52 | Soft-IoU + EM-Merger unit | 2019-04-01 |
| Open-world Text-specified Object Counting | ✓ Link | 8.13 | 10.87 | CounTX (uses arbitrary text input to specify object to count, used "the cars" for CARPK) | 2023-06-02 |
| Drone-based Object Counting by Spatially Regularized Regional Proposal Network | | 16.62 | 22.30 | RetinaNet (2018) | 2017-07-19 |
| A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning | | 21.88 | 36.73 | One-Look Regression (2016) | 2016-09-14 |
| Drone-based Object Counting by Spatially Regularized Regional Proposal Network | | 22.76 | 34.46 | LPN Counting (2017) | 2017-07-19 |
| Focal Loss for Dense Object Detection | ✓ Link | 24.58 | | RetinaNet (2018) | 2017-08-07 |
| Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | ✓ Link | 39.88 | 47.67 | Faster R-CNN (2015) | 2015-06-04 |
| YOLO9000: Better, Faster, Stronger | ✓ Link | 130.40 | 172.46 | YOLO9000opt (2017) | 2016-12-25 |
| You Only Look Once: Unified, Real-Time Object Detection | ✓ Link | 156.00 | 57.55 | YOLO (2016) | 2015-06-08 |