NAV3R: BENCHMARKING NAVIGATION-CONSTRAINED RGB CAPTURE FOR 3D RECONSTRUCTION

Embodied 3D reconstruction requires an agent to decide not only how to reconstruct a scene, but also where to move and which observations to retain. Yet exploration and reconstruction are typically evaluated separately, leaving unclear whether better exploration actually produces better inputs for reconstruction. We introduce NAV3R, a benchmark for navigation-constrained RGB capture and 3D reconstruction. Agents explore unfamiliar indoor scenes under movement and frame budgets, and their retained observations are evaluated jointly by exploration coverage, pose-free geometric reconstruction, and novel-view synthesis. Across 51 scenes from three indoor environments, we benchmark diverse navigation and view-selection policies with multiple RGB reconstruction models. Our results reveal a consistent trade-off: broader exploration improves whole-scene completion and generally benefits novel-view synthesis, but is associated with higher reconstruction error over the observed region. We further find that reconstruction quality depends strongly on acquisition structure, including view overlap, spatial spread, and frame selection. These results show that coverage and reconstruction quality are not interchangeable objectives, motivating joint evaluation of exploration, geometry, and rendering for embodied 3D reconstruction.