Standard DatasetsPerson And Clothes 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 "Person And Clothes Semantic Segmentation Dataset" is designed for the e-commerce, fashion, and media & entertainment industries, featuring a diverse range of internet-collected images with resolutions spanning from 92 x 153 to 3024 x 5381 pixels. This dataset offers detailed instance and semantic segmentation of clothing items and body parts, including new categories like hats, gloves, and shoes, supporting various applications in online retail and fashion technology.
Sample
Specification
Dataset ID
MD-Image-026
Dataset Name
Person And Clothes Semantic Segmentation Dataset
Data Type
ImageVolume
About 197.1k
Data Collection
Internet collected images. Resolution ranges from 92x 153 to 3024 x 5381 pixels.
Annotation
Semantic Segmentation,Instance Segmentation
Annotation Notes
Clothes categories includes backgrounds, hats, hair, sunglasses, coats, skirts, trousers and body parts such as faces, left and right legs, left and right arms, etc. New categories are added: hats, gloves, sunglasses, coats, socks, dresses, shoes.
Application Scenarios
Media & Entertainment;Fashion;E-Commerce
Data Collections
This dataset consists of approximately 197.1k images, each annotated with a variety of clothing categories and body parts. The extensive range of resolutions and detailed segmentation of items like sunglasses, coats, and dresses make it a valuable resource for developing advanced solutions in virtual try-on, personalized shopping experiences, and digital content creation, providing a comprehensive understanding of person and clothing segmentation.
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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