Datasets & Competitions
ShanghaiTechRGBD is a large-scale RGB-D crowd counting dataset including 2,293 pairs of RGB-D images, which were annotated with the heads of 144,512 pedestrians. In addition, to facilitate the verification of the algorithm, the dataset is divided into training and testing sets, which contain 1,193 pairs of images and 1,000 pairs of images, respectively. This dataset is derived from the following paper: 1. Locating_and_Counting_Heads_in_Crowds_With_a_Depth_Prior. 2. Density map regression guided detection network for rgb-d crowd counting and localization. To use this dataset, please cite:D.
- Categories:
155 Views
DroneRGBT dataset consists of 3,600 pairs of RGB-T images, which have annotations for a total of 175,698 pedestrians that were captured by drones. This dataset is split into 1,800 pairs of images for training, and the rest are used for testing, thereby further improving the comprehensiveness of our experimental verification. This dataset is derived from the following paper：Rgb-t crowd counting from drone: A benchmark and mmccn network.To use the dataset, please cite: T. Peng, Q. Li, and P.
- Categories:
192 Views
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.
- Categories:
144 Views