Memory Over Maps: 3D Object Localization Without Reconstruction
Target localization is a prerequisite for embodied tasks such as navigation and manipulation. Conventional approaches rely on constructing explicit 3D scene representations to enable target localization, such as point clouds, voxel grids, or scene graphs. While effective, these pipelines incur substantial mapping time, storage overhead, and scalability limitations. Recent advances in vision-language models suggest that rich semantic reasoning can be performed directly on 2D observations, raising a fundamental question: is a complete 3D scene reconstruction necessary for object localization? In this work, we revisit object localization and propose a map-free pipeline that stores only posed...
| Authors | Rui Zhou, Xander Yap, Jianwen Cao et al. |
|---|---|
| Primary category | cs.RO |
| Published | 20 March 2026 |
| Last updated at source | 20 April 2026 |
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