Enhancing Crowd Counting Model Accuracy through Advanced Density Map Generation Techniques

[yihong1120]

I have been exploring crowd counting methods and have found that the accuracy of pedestrian counting in crowd scenes can be further improved through advanced density map generation techniques. The current methods, such as fixed-size density maps, perspective density maps, and KNN density maps, have their limitations in capturing the intricate details of crowd distribution. I am seeking guidance on implementing more advanced density map generation techniques or exploring alternative approaches to enhance the accuracy of crowd counting models. Additionally, I am interested in understanding how these advanced techniques can be integrated into existing deep learning models for crowd counting. Any insights or resources on this topic would be greatly appreciated.