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Lidar scene completion boosted by semantic labels and visibility info

By PulseAugur Editorial · [2 sources] ·

Researchers have identified simple methods to enhance Lidar semantic scene completion (SSC) performance without altering model architecture. By incorporating semantic pseudo-labels from existing segmentors and adding visibility information to distinguish empty from unknown spaces, older models can become competitive with or even surpass state-of-the-art systems. The study indicates that high-quality semantic priors are a key factor in improving mean Intersection over Union (mIoU) gains. AI

IMPACT Simple data augmentation techniques can significantly improve Lidar scene completion models, potentially reducing the need for complex architectural changes.

RANK_REASON The cluster contains an academic paper detailing research findings.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Lidar scene completion boosted by semantic labels and visibility info

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The cluster contains an academic paper detailing research findings.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch, Gilles Puy, Renaud Marlet, Raoul de Charette ·

    Exploring Easy Boosts for Lidar Semantic Scene Completion

    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…

  2. arXiv cs.CV TIER_1 English(EN) · Raoul de Charette ·

    Exploring Easy Boosts for Lidar Semantic Scene Completion

    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…

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