Indoor Multiple Person & Object Segmentation Dataset

Data Collections

Comprising 7,500 images, this dataset offers a glimpse into diverse indoor settings, captured in dramas from various cultures. Each image includes multiple individuals and objects, annotated for semantic segmentation of human body areas, clothing, accessories, and indoor elements. This dataset is a valuable resource for enhancing applications in internet content and entertainment, providing detailed data for realistic and complex scene understanding.

Data Applitcation

The Indoor Multiple Person & Object Segmentation Dataset is built for training and evaluating AI models in complex indoor environments where multiple people and objects coexist. Typical applications include:

1. Multi-person scene understanding
Enable AI models to accurately parse crowded indoor scenes with 5–6 people per image.

2. Human body & clothing segmentation
Support fine-grained segmentation of body parts, garments, and accessories for content analysis and virtual try-on systems.

3. Media & entertainment AI
Power intelligent video editing, background replacement, character interaction analysis, and drama scene understanding.

4. Smart content moderation & indexing
Improve semantic understanding of indoor images for tagging, retrieval, and recommendation systems.

5. Foundation models & multimodal AI training
Provide realistic, richly annotated indoor scenes for large-scale vision and multimodal models.

Why choose our Indoor Multiple Person & Object Segmentation Dataset

1. Real-world indoor scenes
Collected from diverse drama content, reflecting realistic living environments instead of staged images.

2. Multi-person & multi-object complexity
Each image contains 5–6 people on average, significantly increasing scene complexity for robust model training.

3. Fine-grained semantic annotations
Pixel-level segmentation covering human body areas, clothing & accessories, and indoor objects in a single dataset.

4. Cross-cultural coverage
Includes Asian, American, and English indoor scenarios to improve model generalization.

5. Enterprise-ready data services
Custom data collection, annotation expansion, and label schema adjustments available for production-scale AI projects.

Quality Assurance

Relevant Open Datasets

To supplement this Dataset, you can explore these open datasets for additional resources:

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