English(EN) Exploring Easy Boosts for Lidar Semantic Scene Completion

语义标签和可见性信息提升激光雷达场景补全效果

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-02 17:59

研究人员发现，无需改变模型架构，即可通过简单方法提升激光雷达语义场景补全（SSC）性能。通过引入现有分割器的语义伪标签，并添加可见性信息以区分空空间和未知空间，旧模型可以与最先进的系统竞争，甚至超越它们。研究表明，高质量的语义先验是提高平均交并比（mIoU）增益的关键因素。 AI

影响简单的数据增强技术可以显著改进激光雷达场景补全模型，可能减少对复杂架构更改的需求。

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arXiv cs.CV TIER_1 English(EN) · Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch, Gilles Puy, Renaud Marlet, Raoul de Charette · 2026-06-03 04:00

探索 Lidar 语义场景补全的简易增强方法

arXiv:2606.03992v1 Announce Type: new Abstract: This paper investigates "free lunch" strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectural redesigns. We first demonstrate that endowing input point clouds with semantic…
arXiv cs.CV TIER_1 English(EN) · Raoul de Charette · 2026-06-02 17:59

探索 Lidar 语义场景补全的简易增强方法

This paper investigates "free lunch" strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectural redesigns. We first demonstrate that endowing input point clouds with semantic pseudo-labels from off-the-shelf segmentors sig…