Improving Object Counting with Heatmap Regulation

By Shubhra Aich, Ian Stavness. 2018

36 citations recorded by the source corpus.

In this paper, we propose a simple and effective way to improve one-look regression models for object counting from images. We use class activation map visualizations to illustrate the drawbacks of learning a pure one-look regression model for a counting task. Based on these insights, we enhance one-look regression counting models by regulating activation maps from the final convolution layer of the network with coarse ground-truth activation maps generated from simple dot annotations. We call this strategy heatmap regulation (HR). We show that this simple enhancement effectively suppresses false detections generated by the corresponding one-look baseline model and also improves the performance in terms of false negatives. Evaluations are performed on four different counting datasets --- two for car counting (CARPK, PUCPR+), one for crowd counting (WorldExpo) and another for biological cell counting (VGG-Cells). Adding HR to a simple VGG front-end improves performance on all these benchmarks compared to a simple one-look baseline model and results in state-of-the-art performance for car counting.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computer Vision and Pattern Recognition

Citations in the corpus

Domain Adaptation for Traffic Density Estimation (2021, background): “Some relevant works present in the literature are (Ciampi et al., 2018), (Amato et al., 2019), (Amato et al., 2018), (Aich and Stavness, 2018), (Laradji et al., 2018).”
Counting Vehicles with Deep Learning in Onboard UAV Imagery (2019, methodology): “Dot-annotation is a less time-consuming operation compared with the bounding box one, but the error of our solution is about the half of the one obtained in [10] for the CARPK dataset, and about three”