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602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data

Human body segmentation
different poses
different ages
different races
different collection backgrounds
different scenes.

602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data,The data diversity includes headphones, body, background,and glasses.In terms of annotation, we adpoted segmentation annotations on headphones, body, background and glasses.The data can be used for tasks such as human body segmentation and the behavior detection of Video conference.

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SpecificationsSpecifications
Data size
602 people, 5 images for each person
Collection environment
Office, coffee shop, supermarket, apartment
Race distribution
151 Asian people, 151 black people, 150 Caucasians people, 150  brown people ,ranging from teenager to middle-aged people, (Aged between 16 and 60)
Gender distribution
301 males, 301 females
Data diversity
different poses, different ages, different races, different collection backgrounds
Device
computer, cellphone
Collecting angles
eye-level angle
Data format
the image data format is .jpg, the annotation file (mask) format is .png
Annotation content
segmentation annotation of headphones, body, background, glasses
Accuracy
based on the accuracy of the actions, the accuracy  is more than 97%; Accuracy of semantic segmentation annotation: for each object, the mask edge location errors in x and y directions are less than 5 pixels, and the category label was correctly labeled, which were considered as a qualified annotation; Annotation accuracy: each object is regarded as the unit, annotation accuracy is more than 97%
Sample Sample
  • 602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data
  • 602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data
  • 602 People –3,010 Images Multi-Races Human Body Semantic Segmentation Data
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