Efficient 3D Deep Learning

This repo contains our recent advances in efficient 3D point cloud understanding.

News

[2020-09] We release baseline training code for SPVCNNs and MinkowskiNets in SPVNAS repo, please have a look!

[2020-08] Please check out our ECCV 2020 tutorial on AutoML for Efficient 3D Deep Learning, which summarizes the methods released in this codebase. We also made the hands-on tutorial available in colab.

[2020-07] Our paper Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution is accepted to ECCV 2020.

[2020-03] Our work PVCNN is deployed on MIT Driverless racing cars, please check of this video.

[2019-12] We give the spotlight talk of PVCNN at NeurIPS 2019.

Projects

• PVCNN: Point-Voxel CNN for Efficient 3D Deep Learning
• SPVNAS: Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
• TorchSparse: High-Performance Neural Network Library for Point Cloud Processing