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Computer Vision Datasets

Instantly enhance AI model performance with high quality off-the-shelf datasets.

Task Type

All
10
Age
2
Clothing Detection
2
Clothing Segmentation
1
Event Detection
10
Expression
6
Face Anti-spoofing
6
Face Detection
2
Face Recognition
31
Face Segmentation
1
Facial Landmark
7
Gait Recognition
3
Garbage Classification
1
Gesture Recognition
7
Human Body Attribute
4
Human Body Detection
8
Human Body Landmark
4
Human Body Segmentation
8
Human Body Tracking
3
Human Pose
25
Image Processing
2
Infrared Face
2
Makeup
1
Object Detection and Classification
3
Occluded Face
2
Others
25
Person Re-Identification
4
Pet Recognition
2
Refined Urban Management
4
Scene Understanding
4
Skin Defects
2
Unlabeled Data
12
Vehicle Re-Identification
1
Vehicle Recognition
2
3D Face
5

Modalities

All
10
Image
93
Video
48

4,484 People Multi-race – Infrared Face Recognition Data

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.
Infrared face Binocular camera Multi-race

5,993 People – Infrared Face Recognition Data

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.
Multiple age periods Multiple facial postures Multiple scenes

28,972 Images - Driver Face Detection & Face 96 Landmarks Annotation Data

100 People - Face Detection & Face 96 Landmarks Annotation 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, infrared cameras were applied. In terms of annotation, each individual consists of 274 to 299 photos, with annotations for detected facial bounding boxes and 96 facial landmarks. The data can be used for tasks such as facial detection, 96 facial landmark recognition.
DMS,Drivers Face Detection Facial 96 Landmarks

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)

1,334 People - Driver Gesture Recognition Data

1,334 People - Driver Gesture Recognition Data covers multiple age groups, multiple time periods, and multiple gestures. In terms of acquisition equipment, visible light and infrared binocular cameras are used. Each person collected 18 static gestures and 23 dynamic gestures. Static gestures included fist-clenching gestures and heart-to-heart gestures, and dynamic gestures included index finger clicks and two-finger clicks. This set of driver gesture recognition data can be used for tasks such as driver gesture recognition.
Driving scenes Multiple gestures Multiple age groups Multiple time periods

304 People Multi-race - Driver Behavior Collection Data

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.
dangerous behaviors fatigue behaviors visual movement behaviors multiple ages multiple time periods multiple races RGB and infrared channels In-car Cameras

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

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

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)
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Why off-the-shelf Datasets

  • Copyright

    Copyright

    Clear Coyright and Ready to Check
  • Security

    Security

    Properly Authorized Secure to Use
  • Professional

    Professional

    Designed and produced by AI data experts
  • Diversity

    Diversity

    Collected from a varity of real scenes
  • Cost Effective

    Cost Effective

    More Cost-Efficient Than Tailored Data
  • Efficiency

    Efficiency

    Ready-To-Go Deliver in Seconds
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