Seeing Is Not Measuring: Tool-Augmented Metric Spatial Reasoning for Vision-Language Models
Vision-Language Models (VLMs) describe scenes well but reason poorly about metric 3D structure such as absolute distances, physical sizes, or egocentric directions. We present a modular, predictor agnostic, tool-augmented framework that equips a small VLM (Qwen3.5-4B) with geometric tools: 3D object detection, metric depth estimation, and deterministic solvers for distance, size and bearing. Each object is detected in the camera frame of its own best view, and the tools use that frame's pose to lift every detection into one shared world frame. Moving metric computation out of the model's weights and into explicit solvers yields large gains on three of four ReVSI-Bench tasks: with a strong...
| Authors | Kai Glantz, Clemens Grange |
|---|---|
| Primary category | cs.CV |
| Published | 24 September 2026 |
| Last updated at source | 24 September 2026 |
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