Coarse four-group semantic color coding (RGBB) appended to point clouds before tokenization improves LLM-based structured indoor prediction on Structured3D, SpatialLM, and ARKitScenes, especially for openings and furniture instances.
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SparseGF is a height-aware sparse segmentation framework with context compression that improves robustness of ground filtering in ALS point clouds from urban to natural scenes.
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Coarse Semantic Injection for LLM-Conditioned Structured Indoor Prediction
Coarse four-group semantic color coding (RGBB) appended to point clouds before tokenization improves LLM-based structured indoor prediction on Structured3D, SpatialLM, and ARKitScenes, especially for openings and furniture instances.
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SparseGF: A Height-Aware Sparse Segmentation Framework with Context Compression for Robust Ground Filtering Across Urban to Natural Scenes
SparseGF is a height-aware sparse segmentation framework with context compression that improves robustness of ground filtering in ALS point clouds from urban to natural scenes.