Standard DatasetsHuman And Accessories 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 And Accessories Segmentation Dataset" is a valuable resource for the apparel, e-commerce, and media & entertainment industries, featuring internet-collected images with resolutions ranging from 584 x 429 to 3744 x 5616. This dataset is rich in diversity, encompassing a wide array of accessories like mobile phones, suitcases, skateboards, and animals, all annotated for semantic segmentation.
Sample
Specification
Dataset ID
MD-Image-017
Dataset Name
Human And Accessories Segmentation Dataset
Data Type
ImageVolume
About 74.3k
Data Collection
Internet collected images.Resolution ranges from 584 x 429 to 3744 x 5616.
Annotation
Semantic Segmentation
Annotation Notes
The dataset contains many types of accessories, such as mobile phones, suitcases, skateboards, motorcycles, bicycles, horses, cattle, dogs, etc.
Application Scenarios
Media & Entertainment;Apparel;E-Commerce
Data Collections
This dataset includes approximately 74.3k images, capturing humans in various settings alongside a broad spectrum of accessories and animals, such as motorcycles, bicycles, and pets. The detailed semantic segmentation annotations provide a deep understanding of the interaction between people and their accessories, making it an excellent tool for developing advanced applications in fashion, online retail, and entertainment content creation.
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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