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October 3, 2025Open Access

RangeSAM: Leveraging Visual Foundation Models for Range-View repesented LiDAR segmentation

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Range-view segmentation with visual foundation models demonstrates improved performance for LiDAR segmentation tasks.
The approach modifies SAM2 architecture to enhance spatial dependencies present in LiDAR range images.
Efficient 2D feature extraction enables faster and simpler deployment of segmentation pipelines.
The framework achieves competitive results on SemanticKITTI while optimizing for range-view representations.

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This framework demonstrates enhanced LiDAR segmentation performance in range-view using VFMs, highlighting efficiency and accuracy.

Kühn et al. (2025) studied this question.

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