3ViewSense uses orthographic views and a Simulate-and-Reason mechanism to let vision-language models significantly outperform baselines on occlusion-heavy counting and view-consistent spatial reasoning
Through diagnostic analyses, the work locates the bottleneck of vision-language models' spatial weakness in a missing view-consistent spatial interface rather than insufficient visual features or weak reasoning, and introduces 3ViewSense, a framework that grounds spatial reasoning in orthographic views and uses a Simulate-and-Reason mechanism to align egocentric perception with allocentric references, enabling explicit mental rotation and reconstruction; it significantly outperforms existing baselines on spatial reasoning benchmarks, with consistent gains on occlusion-heavy counting and view-consistent spatial reasoning, and also improves the stability and consistency of spatial descriptions.