RGBT-CC

RGB-T Crowd counting. RGBT-CC dataset is made up of 2,030 pairs of RGB-T images, each having a resolution of 640×480, and these images were captured under different scene circumstances and lighting conditions.  A total of 138,389 pedestrians are precisely annotated in this dataset, and there are roughly 68 pedestrians on average in each image.  It is divided into three separate subsets: training is performed using 1,030 images, 200 images are used for validation, and 800 images are for testing. The dataset is derived from the following CVPR paper:Cross-modal collaborative representation learning and a large-scale rgbt benchmark for crowd counting.When using this dataset, please cite: L. Liu, J. Chen, H. Wu, G. Li, C. Li, and L. Lin,  "Cross-modal collaborative representation learning and a large-scale rgbt benchmark for crowd counting,"  in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2021, pp. 4823-4833.