High-Quality Training Datasets

This Multi-view Person Tracking Dataset features 4,001 unique individuals captured across both indoor and outdoor environments, including supermarkets, shopping malls, and residential communities, etc.. Each person is recorded by at least seven distinct cameras, providing rich cross-view perspectives. The dataset offers high diversity in age groups, time of day, camera viewpoints, human orientations, and body postures. It is ideal for computer vision tasks such as multi-camera person tracking, cross-view person re-identification (ReID), single object tracking, and multi-view object detection. This dataset is highly suitable for developing and evaluating advanced tracking algorithms in complex real-world scenarios.

Large-scale multi-view tracking dataset of 10,114 people captured in indoor and outdoor surveillance scenes. Includes diverse ages and genders.Each subject is annotated with human body bounding boxes, human body+riding object bounding boxes, and 21 human body attributes. This data can be used for human multi-view tracking, person re-identification (Re-ID), pedestrian analysis, and AI/computer vision model training.

212 Person Indoor Surveillance Tracking Dataset – 48K Images for Object Tracking & Human Detection. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different shooting angles, different human body orientations and postures. For annotation, we adpoted rectangular bounding boxes annotations on human body. This dataset can be used for multiple object tracking and other tasks.