5,521 People - Re-ID Data in Surveillance Scenes

40 People – Safety Dressing Collection Data

40 People – Safety Dressing Collection Data. Each subject collects 24 videos, each video lasts about 30 seconds. The gender distribution includes male and female, the age distribution is young and middle-aged. Collecting scenes include 2 indoor scenes and 2 outdoor scenes. The collecting angles are looking down angle, looking up angle. The data diversity includes multiple scenes, multiple actions, multiple angles, multiple safety dressing equipment. The data can be used for tasks such as detection and recognition of safety dressing for power personnel.

Safety dressing indoor scene outdoor scenes multiple scenes multiple actions multiple angles multiple safety dressing equipment detection and recognition of safety dressing for power personnel

2,769 People - CCTV Re-ID Data in Europe

2,769 People – CCTV Re-ID Data in Europe. The data includes males and females, the race distribution is Caucasian, black, Asian, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different cameras, different human body orientations and postures. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. This data can be used for re-id and other tasks.

European CCTV Re-ID different age groups different time periods different cameras different human body orientations and postures the human body rectangular bounding boxes the rectangular bounding boxes

65 People –15,204 Videos of Sports and Fitness Video Data

65 People –15,204 Videos of Sports and Fitness Video Data. The data collection scene is indoor scenes. The race distribution is Asian, black and Caucasian; the age distribution is young and middle-aged people. The collection device is IR and RGB cameras. The dataset diversity includes different races, different age groups, different shooting angles, different collection distances, different human body orientations, different costumes and various fitness actions. The data can be used for tasks such as human behavior recognition and human segmentation in fitness scenes.

Sports and fitness IR and RGB cameras human behavior recognition human segmentation fitness scenes.

11,130 People - Re-ID Data in Real Surveillance Scenes

11,130 People - Re-ID Data in Real Surveillance Scenes. The data includes indoor scenes and outdoor scenes. The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different shooting angles, different human body orientations and postures, clothing for different seasons. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. This data can be used for re-id and other tasks.

different ages different time periods different cameras different human body orientations and postures different ages collecting environment

189 Videos-Electric Bicycle Entering Elevator Data

189 Videos-Electric Bicycle Entering Elevator Data，the total duration is 1 hour 58 minutes 40.72 seconds. The data covers different types of elevators, different types of electric bicycles, different time periods. The data can be used for tasks such as electric bicycle detection, electric bicycle recognition .

different types of elevators different types of electric bicycles different types of non-electric bicycles different time periods

5,808 People - Human Pose Recognition Data

5,808 People - Human Pose Recognition Data. This dataset includes indoor and outdoor scenes.This dataset covers males and females. Age distribution ranges from teenager to the elderly, the middle-aged and young people are the majorities. The data diversity includes different shooting heights, different ages, different light conditions, different collecting environment, clothes in different seasons, multiple human poses. For each subject, the labels of gender, race, age, collecting environment and clothes were annotated. The data can be used for human pose recognition and other tasks.

Different shooting heights different ages different light conditions different collecting environment clothes in different seasons multiple human poses

10,034 People - Re-ID Data in Surveillance Scenes

10,034 People - Re-ID Data in Surveillance Scenes. The data includes supermarket (inside supermarket and at the gate of the supermarket) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 15 attributes of human body were annotated.The data can be used for re-id and other tasks.

Surveillance scenes Re-ID multiple time periods multiple ages human body rectangular bounding boxes attributes annotation

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes

208,914 Bounding Boxes – Human Body Attributes Data in Surveillance Scenes. The data includes indoor (shopping mall) and outdoor (street, the gate of shopping mall and square) scenes. The data includes males and females and the age distribution is from children to the elderly. In this dataset, the rectangular bounding boxes and 19 attributes of human body were annotated. The data can be used for person attributes recognition.

indoor and outdoor scenes human body bounding boxes appendage bounding boxes surveillance camera multiple age groups human body attributes

5,521 People - Re-ID Data in Surveillance Scenes

Surveillance scenes Re-ID different age groups different time periods different shooting angles different human body orientations and postures clothing for different seasons human body rectangular bounding boxes attributes annotation

Surveillance scenes

Re-ID

different age groups

different time periods

different shooting angles

different human body orientations and postures

clothing for different seasons

human body rectangular bounding boxes

attributes annotation