Computer Vision Datasets

4,484 people multi-race – infrared face recognition data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The race distribution includes Asian, Black, Caucasian and Brown people. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is DV-DH4,044S305AD. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

5,993 People – Infrared Face Recognition Data. The collecting scenes of this dataset include indoor scenes and outdoor scenes. The data includes male and female. The age distribution ranges from child to the elderly, the young people and the middle aged are the majorities. The collecting device is realsense D453i. The data diversity includes multiple age periods, multiple facial postures, multiple scenes. The data can be used for tasks such as infrared face recognition.

The Driver Gesture Recognition Dataset contains recordings from 1,334 participants across diverse age groups, time periods and multiple gestures. Each person performed 18 static gestures(such as fist-clenching gestures and heart-to-heart gestures) and 23 dynamic gestures(including index finger clicks and two-finger clicks). In terms of acquisition equipment, visible light and infrared binocular cameras are used. This dataset is ideal for tasks such as driver monitoring, gesture recognition in vehicles, human-computer interaction, and driver assistance systems.

This dataset contains 28,972 high-resolution infrared images of 100 individuals in driver scenarios, each annotated with face bounding boxes and 96 facial landmarks. The participants vary in age and race (Caucasian, Black, Indian), and the data reflects realistic driving behaviors including fatigue, distraction, and visual movement. Each subject contributes between 274 and 299 images. Infrared cameras were used to ensure visibility under varying lighting conditions. This dataset is suitable for facial detection, keypoint tracking, driver monitoring system (DMS) development, and other computer vision applications. All data complies with GDPR, CCPA, and PIPL regulations.

The 1,444 passenger behavior recognition data covers multiple ages, time periods and light exposure. Passenger behavior includes passenger normal behavior, passenger abnormal behavior (passenger motion sickness behavior, passenger sleepiness behavior, passenger lost children & items behaviors). In terms of acquisition equipment, visible and infrared binocular cameras are used. This set of passenger behavior identification data can be used for passenger behavior analysis and other tasks.

304 People Multi-race - Driver Behavior Collection Data. The data includes multiple ages, multiple time periods and multiple races (Caucasian, Black, Indian). The driver behaviors includes dangerous behavior, fatigue behavior and visual movement behavior. In terms of device, binocular cameras of RGB and infrared channels were applied. This data can be used for tasks such as driver behavior analysis.

1,350 People-Driver Behavior Identification Data. The data includes multiple ages, multiple time periods and multiple lighting. The driver behaviors includes Dangerous behavior, fatigue behavior and visual movement behavior. In terms of device, binocular cameras of RGB and infrared channels were applied. This data can be used for tasks such as driver behavior analysis.

Seven facial expressions recognition data of 1,323 drivers cover multiple ages, multiple time periods and multiple expressions. In terms of acquisition equipment, visible and infrared binocular cameras are used. This set of driver expression recognition data can be used for driver expression recognition analysis and other tasks.

122 People - Passenger Behavior Recognition Data. The data includes multiple age groups, multiple time periods and multiple races (Caucasian, Black, Indian). The passenger behaviors include passenger normal behavior, passenger abnormal behavior(passenger carsick behavior, passenger sleepy behavior, passenger lost items behavior). In terms of device, binocular cameras of RGB and infrared channels were applied. This data can be used for tasks such as passenger behavior analysis.