A geometric lens for vision-language models
GeoVLM introduces a geometric visual interface layer for Vision Language Models — enabling spatial reasoning, structural understanding, and intuitive visual interaction that goes beyond bounding boxes.
Beyond bounding boxes
Current vision-language models interact with images through crude spatial primitives — bounding boxes, point coordinates, segmentation masks. But human visual understanding is fundamentally geometric.
Geometric Primitives
Lines, polygons, curves, and spatial graphs as first-class interaction objects.
Structural Reasoning
Understand relationships between scene elements through topology and geometry.
VLM Integration
A drop-in layer compatible with existing vision-language model architectures.
Where geometry meets vision
Architectural Analysis
Understand building structures, room layouts, and spatial relationships in architectural images with geometric precision.
Scene Graph Generation
Automatically generate rich scene graphs that capture spatial, structural, and semantic relationships between objects.
Robotic Perception
Give robotic systems a geometric understanding of their environment for better navigation and manipulation.
3D Understanding
Infer 3D structure and relationships from 2D images, bridging the gap between flat images and spatial reality.
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GeoVLM is being built by 14AI — an indie studio exploring the intersection of geometry and visual AI.