Idea
A large-scale annotated floor plan dataset and pipeline enabling AI developers and researchers to build spatial intelligence applications.
Research Paper
Core Innovation
This paper introduces ResPlan, a dataset of 17,000 residential floor plans with precise architectural annotations and multiple format support. It surpasses existing datasets in visual fidelity and structural diversity and provides an open-source pipeline for data refinement. This enables more accurate and scalable spatial AI research and applications.
Market Size (TAM)
$2–10B TAM, $1–2B SAM; assumption: growing demand for spatial AI, robotics, VR/AR, and simulation technologies.
Potential Customers & Pain Points
- AI Developers Needing High-Quality Spatial Data
- Robotics Companies Requiring Detailed Indoor Maps
- VR/AR Developers Seeking Realistic Environments
- Game Developers Needing Diverse Floor Plan Assets
- Researchers Lacking Large-Scale Annotated Architectural Data
Business Model
Subscription-based API access to dataset and tools; enterprise licensing for large-scale commercial use; consulting for custom dataset integration.
Competitive Landscape
- Matterport
- OpenFloorPlan
- FloorNet
Implementation Challenges
- Data Licensing and Usage Restrictions
- Integration Complexity with Existing AI Pipelines
- Maintaining Dataset Quality and Updates
Validation Strategy
- Pilot integration with robotics navigation systems
- Partnership with VR/AR developers for environment testing
- Benchmarking dataset utility in generative AI models
Research Paper Overview
ResPlan: A Large-Scale Vector-Graph Dataset of 17,000 Residential Floor Plans
Summary
ResPlan is a comprehensive dataset of 17,000 detailed residential floor plans with precise annotations of architectural elements and functional spaces. It offers enhanced visual fidelity and structural diversity compared to existing datasets, supports multiple formats for easy integration, and includes an open-source pipeline for data refinement. ResPlan enables advanced spatial AI research and applications in robotics, reinforcement learning, generative AI, VR/AR, simulations, and game development.