What is sparse convolution and where is it used in vision systems?

Sparse convolution operates only on non-empty spatial locations, improving efficiency for sparse data.

In many vision problems like 3D point clouds or LiDAR data, most spatial locations are empty. Sparse convolution avoids computing over zero-valued regions by only processing active voxels. This reduces memory and compute significantly while maintaining accuracy in sparse domains.