In our NeurIPS’19 paper [1], we propose Point-Voxel CNN (PVCNN), an efficient 3D deep learning method for various 3D vision applications. Here we show the 3D object segmentation demo which runs at 20 FPS on Jetson Nano. Note that the most efficient previous model, PointNet, runs at only 8 FPS. We al…

[image] zhijianliu: GitHub - mit-han-lab/pvcnn: [NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning Excellent efficiency. I would like to run the code on my jetson nano 4gb too, I wonder whether the project you shared on github ( GitHub - mit-han-lab/pvcnn: [NeurIPS 2019, …

3D Part and Scene Segmentation with Point-Voxel CNN on NVIDIA Jetson

Robotics & Edge Computing Jetson Systems Jetson Projects

dusty_nv January 27, 2020, 5:46pm 2

Great work, very exciting! Thanks for sharing - we enjoy following your lab’s research since the Temporal Shift Module publication.

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3D Part and Scene Segmentation with Point-Voxel CNN on NVIDIA Jetson

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