Standard DatasetsHuman Body Semantic Segmentation Dataset
Advanced datasets and Generative AI are revolutionizing the fashion and e-commerce industries, providing customized experiences and immersive interactions for shoppers worldwide.Our datasets provide valuable insights into fashion trends, styles, and consumer preferences, enabling businesses to deliver personalized shopping experiences.
The "Human Body Semantic Segmentation Dataset" serves the fashion, internet, and entertainment sectors with a diverse collection of human body images. This dataset, featuring an even distribution across genders and ages from various countries, is ideal for applications requiring detailed analysis of human postures, hairstyles, and different scenarios. With fine labeling of 19 human body areas, it facilitates advanced semantic segmentation tasks.
Sample
Specification
Dataset ID
MD-Image-005
Dataset Name
Human Body Semantic Segmentation Dataset
Data Type
ImageVolume
About 100k
Data Collection
Internet collected human body images with evenly distributed gender and age, covering multiple countries, variable posture , hairstyle and scenarios.
Annotation
Semantic Segmentation
Annotation Notes
Fine labeling of 19 human body areas, including face, left/right arm, left/right leg, hat, hair, coat and so on.
Application Scenarios
Media & Entertainment;Internet;Social Media;Fashion & Apparel
Data Collections
Comprising approximately 100k images, this dataset offers a global perspective on human diversity, capturing a wide array of postures, hairstyles, and scenarios. Each image is annotated with fine detail across 19 body areas, supporting nuanced segmentation for fashion, media, and social media applications, and providing a comprehensive tool for realistic and precise human body analysis.
Quality Assurance
Relevant Open Datasets
To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:
Fashionpedia [Learn more]
This dataset includes 48,825 clothing images annotated with segmentation masks and fine-grained attributes, built upon an expertly crafted ontology that encompasses 27 main apparel categories and 19 apparel parts. It's designed to advance tasks combining both detection and attributes classification in the fashion domain.
DeepFashion2 [Learn more]
A comprehensive fashion dataset containing 491K images of 13 popular clothing categories from both commercial and consumer sources. Each item is meticulously labeled with attributes such as scale, occlusion, viewpoint, category, and style, making it a versatile benchmark for clothing image understanding.
DeepFashion [Learn more]
This dataset boasts around 800K diverse fashion images with rich annotations, including 46 categories, 1,000 descriptive attributes, bounding boxes, and landmark information. The variety ranges from well-posed product images to consumer photos, providing a broad spectrum for fashion image analysis.
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