Standard DatasetsOutdoor Multi-person Panoptic 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 "Outdoor Multi-person Panoptic Segmentation Dataset" is tailored for the visual entertainment industry, featuring a collection of internet-collected outdoor images with resolutions ranging from 1543 x 2048 to 3072 x 2304 pixels. This dataset focuses on panoptic segmentation, encompassing multiple people and distinguishable objects such as those on individuals, buildings, vehicles, and plants. Each identifiable instance within the images is annotated, providing a comprehensive view of outdoor scenes.
Sample
Specification
Dataset ID
MD-Image-086
Dataset Name
Outdoor Multi-person Panoptic Segmentation Dataset
Data Type
ImageVolume
About 26k
Data Collection
Internet collected images. Resolution is from 1543 x 2048 to 3072 x 2304.
Annotation
Panoptic Segmentation
Annotation Notes
This dataset contains multiple people and obvious objects on people, buildings, vehicles, plants, etc. with panoptic segmentation ,annotate each identifiable instance in the image.
Application Scenarios
Visual Entertainment
Data Collections
This dataset comprises approximately 26k images, each meticulously annotated to include every identifiable instance, whether it's a person, an object on a person, or elements of the surrounding environment like buildings, vehicles, and vegetation. The panoptic segmentation approach offers a holistic understanding of outdoor scenes, making this dataset invaluable for developing and enhancing content in visual entertainment, such as in film production, game development, and augmented reality applications, by providing detailed data for realistic and immersive scene 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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