Computer Vision Training Dataset - Nexdata

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Task Type

All

7

Age

2

Clothing Detection

2

Clothing Segmentation

1

Event Detection

9

Expression

6

Face Anti-spoofing

6

Face Recognition

29

Face Segmentation

1

Facial Landmark

4

Gait Recognition

3

Garbage Classification

1

Gesture Recognition

6

Human Body Attribute

4

Human Body Detection

6

Human Body Landmark

3

Human Body Segmentation

7

Human Body Tracking

3

Human Pose

25

Image Processing

1

Infrared Face

1

Makeup

1

Object Detection and Classification

3

Occluded Face

2

Others

22

Person Re-Identification

4

Pet Recognition

2

Refined Urban Management

4

Scene Understanding

4

Skin Defects

1

Unlabeled Data

11

Vehicle Re-Identification

1

Vehicle Recognition

2

3D Face

4

Modalities

All

7

Image

85

Video

46

9,000 Images of 180 People - Driver Gesture 21 Landmarks Annotation Data

9,000 Images of 180 People - Driver Gesture 21 Landmarks Annotation Data. This data diversity includes multiple age periods, multiple time periods, multiple gestures, multiple vehicle types, multiple time periods. For annotation, the vehicle type, gesture type, person nationality, gender, age and gesture 21 landmarks (each landmark includes the attribute of visible and invisible) were annotated. This data can be used for tasks such as driver gesture recognition, gesture landmarks detection and recognition.

DMS driver gesture gesture 21 landmarks static gesture dynamic gesture driver gesture recognition gesture landmarks detection gesture landmarks recognition

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 n-car Cameras RGB and infrared channels feeling passion sentiment excitement sensation affection intensity ardor sensibility fervor vehemence love response warmth zeal emotional pathos agitation spirit affectivity enthusiasm fervency perturbation impression sympathy sadness sentimentality thrill eagerness poignancy commotion emotionalism fire soul animation emotionality responsiveness sensitiveness disturbance energy expression tenderness pitifulness plaintiveness poignance sentiments vibes anger empathy feelings

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 acquisition data driver behavior acquisition driver data acquisition driver behavior data wide-angle camera

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.

Driver expression data driver expression data collection driver expression recognition data human pose data

1,335 People - Driver Gesture Recognition Data

1,335 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.

Driver Gesture Collection Data Driver Gesture Collection Driver Collection Data Driver Gesture Data

103,282-Images Driver Behavior Annotation Data

103,282-Images Driver Behavior Annotation Data. The data includes multiple ages, multiple time periods and behaviors (Dangerous behaviors, Fatigue behaviors, Visual movement behaviors). In terms of annotation, 72 facial landmarks (including pupils), face attributes, gesture bounding boxes, seatbelt bounding boxes, pupil landmarks and behavior categories were annotated in the data. This data can be used for tasks such as driver behavior analysis.

dangerous behaviors fatigue behaviors visual movement behaviors 72 facial landmarks face attributes gesture bounding boxes seatbelt bounding boxes pupil landmarks behavior categories multiple ages multiple time periods In-car Cameras RGB and infrared channels.emini pair couple matches two brace pairs deuce double doubles duality twin match combine twosome duo dyad mates duet duplicate gemini the twins similitude yoke binaries counterparts mate analogs counterpart couples doublets look-alike parallel span deuces mirror images brothers clone duplexes nuts rocks alter egos balls clones combo doublet dyads equivalents join pair-offs plums

1,003 People-Driver Behavior Collection Data

1,003 People-Driver Behavior Collection Data. The data includes multiple ages and multiple time periods. 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 In-car Cameras RGB and infrared channels

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