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arXiv Computer Vision By Hongqiang Lin, Tianle Wang, Shuiwang Li, Dongxu Zhang, Yiding Sun, Zihao Guo, Dongfu Yin

Partition-Invariant Tuning for 3D Scene Understanding

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The paper introduces PointPiT, a partition‑invariant tuning framework designed for scene‑level point cloud understanding. It combines a Scene‑aware Structural Adapter (SSA) that fuses local geometry with global context, and Gradient Subspace Optimization (GSO) that selects stable update directions to reduce partition‑induced representation shifts. Experiments on multiple benchmarks show that PointPiT matches or surpasses full fine‑tuning while using less than 1% of the backbone’s parameters, achieving state‑of‑the‑art performance among parameter‑efficient fine‑tuning methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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