Semantics
Niantic Spatial’s semantics capabilities uses per-pixel segmentation and understanding to deliver real-time contextual awareness, enabling humans, robots, and AI agents to query environments, analyze spatial relationships, and make decisions at scale.
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Aerial view
Semantic Understanding
Niantic’s semantics capabilities use AI-powered semantic analysis to classify every pixel of the physical world into meaningful categories such as ground, sky, water, and buildings that deliver real-time contextual awareness. This allows humans, robots, AI agents, and enterprise systems to interpret environments, assess spatial relationships, and make data-driven decisions safely and at scale.
With semantic awareness, organizations can enable advanced use cases, such as remote risk assessment for insurance underwriting, power line monitoring and compliance, and utility route planning and permitting.
Categories include:
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Water, sky, ground (natural and artificial)
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Buildings and infrastructure
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Foliage and vegetation
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Pixel-level semantic understanding of environments
Ground-level view
Object Detection
Niantic’s object detection capabilities use AI-based computer vision models to identify and track objects in real time. This enables dynamic monitoring, interaction, and automation for enterprise workflows, whether on mobile devices, head-mounted displays, or autonomous systems.
With object awareness, humans, robots, and AI agents can locate assets, detect obstacles, and respond to changes in the environment to improve safety and operational efficiency.
Key Features
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Detection of over 200 object categories
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Real-time bounding box tracking
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Support for multi-object and multi-class detection
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Integration with VPS and semantics for richer context