maadaa ai

Standard Datasets

Eastern Asia Single-person Portrait Matting 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.

Our "Eastern Asia Single-person Portrait Matting Dataset" targets the nuanced requirements of the fashion, internet, and entertainment sectors, featuring single-person portraits from Eastern Asia in a variety of settings including indoor, outdoor, street, and sport. This dataset is specially curated for pixel-level fine segmentation tasks, capturing diverse postures and scenarios.

Sample

Specification

Dataset ID

MD-Image-004

Dataset Name

Eastern Asia Single-person Portrait Matting Dataset

Data Type

Image

Volume

About 50kk

Data Collection

Internet collected Eastern Asia person portrait image with variable posture, in variable scenarios like indoor, outdoor, street, sport, etc.

Annotation

Contour Segmentation,Segmentation

annotationNotes

Pixel-level fine segmentation.

Application Scenarios

Media & Entertainment;Internet;Social Media;Fashion & Apparel

Data Collections

This dataset includes 50k portraits, each reflecting the diverse lifestyles and environments of Eastern Asia. With scenarios ranging from serene indoors to dynamic street scenes, each image is meticulously annotated for contour segmentation, offering a rich resource for fashion, media, and social media applications, emphasizing pixel-level detail for enhanced realism in 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.