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HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-Scale Point Clouds
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We present a novel deep neural network architecture for end-to-end scene flow estimation that directly operates on large-scale 3D point clouds. Inspired by Bilateral Convolutional Layers (BCL), we propose novel DownBCL, Up-BCL, and CorrBCL operations that restore structural information from unstructured point clouds, and fuse information from two consecutive point clouds. Operating on discrete and sparse permutohedral lattice points, our architectural design is parsimonious in computational
doi:10.1109/cvpr.2019.00337
dblp:conf/cvpr/GuWWLW19
fatcat:dmurypc5r5fknkoslwlqdskxci