Annotated Driver Hand Gesture Dataset – 180 People, 9,000 Images

3D Synthetic Sensor Dataset for DMS – Images, Video & Point Clouds

This 3D high-fidelity synthetic dataset simulates real-world Driver Monitoring System (DMS) environments using photorealistic 3D scene modeling. It includes multi-modal sensor outputs such as camera images, videos, and point clouds, all generated through simulation. The dataset is richly annotated with object classification, detection, and segmentation labels, as well as human pose data (head, eye, arm, and leg position/orientation), camera parameters, and temporal metadata such as illumination and weather conditions. Ideal for training and evaluating models in autonomous driving, robotics, driver monitoring, computer vision, and synthetic perception tasks.

3D synthetic data driver monitoring synthetic dataset autonomous driving synthetic data high-fidelity simulation dataset synthetic point cloud data camera simulation dataset human pose synthetic dataset synthetic lidar dataset 3D environment modeling robotics synthetic data DMS dataset

Driver Face Detection Dataset – 28,972 Images with 96 Landmark Annotations

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.

driver face detection dataset 96 facial landmarks dataset infrared face image dataset facial keypoint annotation driver fatigue detection data distracted driver dataset computer vision driver monitoring face bounding box dataset DMS dataset driver behavior image dataset

3,360 Images of 168 People - Passenger Behavior Human Body Detection Data

3,360 Images of 168 people - passenger behavior human body detection data. The data scenes are the In-cabin camera scenes. The gender distribution is male and female, and the age distribution is mainly young and middle-aged. Data diversity includes multiple age groups, multiple time periods, multiple lights, and multiple passenger behaviors. In terms of content collection, passengers' normal behavior, calling behavior and smoking behavior are collected. In terms of labeling, the human rectangular box is labeled. The data can be used for tasks such as human body detection of passenger behavior. 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.

Passenger behaviors Normal behavior Calling behavior Smoking behavior Human body detection

1,334 People Driver Gesture Recognition Dataset – Static & Dynamic Gestures for Automotive AI

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.

driver gesture dataset automotive AI dataset in-car gesture recognition driver monitoring dataset human computer interaction dataset static and dynamic gestures vehicle hand gesture dataset infrared camera dataset visible light gesture data driver assistance AI

1,323 Drivers - 7 Expression Recognition Data

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.

Multiple expressions Multiple ages Multiple time periods

1,4444 People - Passenger Behavior Recognition Data

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.

Multiple age groups Multiple time periods Multiple behaviors (normal behaviors Carsick behaviors Sleepy behaviors Lost items behaviors)

1,350 People Driver Behavior Identification Data

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.

Driver behavior Dangerous behavior Fatigue behavior Visual movement behavior Multiple ages Multiple time periods

122 People - Passenger Behavior Recognition Data

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.

Multiple age groups Multiple time periods Multiple behaviors (normal behaviors Carsick behaviors Sleepy behaviors Lost items behaviors)

Annotated Driver Hand Gesture Dataset – 180 People, 9,000 Images

driver gesture dataset hand gesture landmark dataset 21 keypoints hand annotation driver monitoring system data gesture recognition dataset driver pose dataset in-vehicle gesture recognition autonomous vehicle hand data driver gesture AI training gesture landmark detection dataset

driver gesture dataset

hand gesture landmark dataset

21 keypoints hand annotation

driver monitoring system data

gesture recognition dataset

driver pose dataset

in-vehicle gesture recognition

autonomous vehicle hand data

driver gesture AI training

gesture landmark detection dataset