将人脸计数框架拓展至汽车计数，兼顾数量与位置估计。
Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework
- 用CLIP-EBC框架处理汽车密度图生成
- 在CARPK数据集上达第二好性能
- 引入K-means加权聚类定位车辆
本文研究了原本用于人群计数的CLIP-EBC框架在汽车对象计数中的适用性，采用CARPK数据集进行实验。结果表明，该模型性能仅次于现有最佳方法，位居第二。此外，提出基于预测密度图的K-means加权聚类方法，实现对物体位置的估计，显示出该框架向定位任务扩展的潜力。
原文摘要 · Abstract (English)
In this paper, we investigate the applicability of the CLIP-EBC framework, originally designed for crowd counting, to car object counting using the CARPK dataset. Experimental results show that our model achieves second-best performance compared to existing methods. In addition, we propose a K-means weighted clustering method to estimate object positions based on predicted density maps, indicating the framework's potential extension to localization tasks.
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