arXiv Computer Vision September 30, 2026 By Liang Peng, Shizhuo Mu, Bohan Tan, Wenyuan Wang, Chen Zhao, Xingping Dong, Heng Fan, Libo Zhang, Bo Du

PGL-3D: Towards Progressive Geometric Learning for 3D Visual Query Localization

Read the original on arXiv Computer Vision →

PGL-3D introduces a progressive geometric learning framework for 3D visual query localization, where intermediate cuboids guide feature aggregation and refinement. The method predicts a complete cuboid for each proposal, selects reference observations via Query‑Tube‑Memory, pools query‑conditioned features, and re‑predicts refined cuboids. A training‑only objective, ST‑D9O, supervises cuboid geometry at every stage, yielding significant performance gains over prior baselines.

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