GRCA uses emitter-centric geometric culling of rays per triangle to accelerate LiDAR simulation in arbitrarily dynamic scenes, reporting up to 14.55x speedup over Embree and 7.97x over OptiX.
Journal of Graphics Tools 3(1):43–46
2 Pith papers cite this work. Polarity classification is still indexing.
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EdgeFormer converts point cloud edge detection into local-patch point classification with a transformer and reports competitive results against six baselines.
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Geometrically Approximated Modeling for Emitter-Centric Ray-Triangle Filtering in Arbitrarily Dynamic LiDAR Simulation
GRCA uses emitter-centric geometric culling of rays per triangle to accelerate LiDAR simulation in arbitrarily dynamic scenes, reporting up to 14.55x speedup over Embree and 7.97x over OptiX.
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EdgeFormer: local patch-based edge detection transformer on point clouds
EdgeFormer converts point cloud edge detection into local-patch point classification with a transformer and reports competitive results against six baselines.