Standard Datasets

Indoor Objects 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 "Indoor Objects Segmentation Dataset" serves the advertisement, gaming, and visual entertainment sectors, offering high-resolution images ranging from 1024 × 1024 to 3024 × 4032. This dataset includes over 50 types of common indoor objects and architectural elements, such as furniture and room structures, annotated for instance, semantic, and contour segmentation.

Sample

Specification

Dataset ID

MD-Image-013

Dataset Name

Indoor Objects Segmentation Dataset

Data Type

Image

Volume

About 51.6k

Data Collection

Internet access, resolution ranges from 1024 × 1024 to 3024 × 4032

Annotation

Semantic Segmentation,Instance Segmentation,Contour Segmentation

Annotation Notes

It includes more than 50 kinds of common indoor living objects, such as beds, pillows, desk lamps, cabinets, tables, computer monitors, as well as architectural structures such as ceilings, floors, walls, windows and doors.

Application Scenarios

Game;Advertisement;Visual Entertainment

Data Collections

With approximately 51.6k images, this dataset provides a detailed look at a variety of indoor living objects and architectural features. It covers everything from beds and pillows to computer monitors, along with structural elements like ceilings and windows. Each item is meticulously annotated for comprehensive segmentation tasks, making it an essential resource for creating realistic environments in advertisements, games, and visual entertainment content.

Quality Assurance

Relevant Open Datasets

To supplement our Face Parsing Dataset, users can explore these open datasets for additional resources:

FASSEG Repository [Learn more]

This collection offers datasets for frontal face segmentation (Frontal01 and Frontal02) and a dataset for faces in multiple poses (Multipose01).These datasets can be valuable for training models to perform face segmentation in different orientations and conditions.

Related products

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