Submanifold Sparse Convolutional Networks

Convolutional network are the de-facto standard for analysing spatio-temporal data such as images, videos, 3D shapes, etc. Whilst some of this data is naturally dense (for instance, photos), many other data sources are inherently sparse. Examples include pen-strokes forming on a piece of paper, or (colored) 3D point clouds that were obtained using a LiDAR scanner or RGB-D camera.

Data and Resources

Cite this as

Benjamin Graham, Laurens van der Maaten (2024). Dataset: Submanifold Sparse Convolutional Networks. https://doi.org/10.57702/thr7xqjr

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Defined In https://doi.org/10.48550/arXiv.1706.01307
Author Benjamin Graham
More Authors
Laurens van der Maaten