# traveller59/spconv

Spatial Sparse Convolution Library

Repository: https://github.com/traveller59/spconv
Canonical: https://ross.abutalabs.com/products/spconv
Language: Python
License: Apache-2.0
License Family: permissive
Topics: point-cloud
Last push: 2024-12-15T15:41:19+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2783, "days_push": 626, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2291, forks 425 (observed 2026-08-28T04:06:34.964180+00:00)

## What it is
SpConv is a spatially sparse convolution library for deep learning on 3D point clouds and sparse tensors, distributed as PyPI packages with CPU and multiple CUDA builds. It provides fast sparse convolution primitives commonly used in LiDAR-based 3D object detection networks.

## Use cases
- run sparse convolutions on 3D point clouds
- build lidar-based 3d object detection models
- process sparse voxel grids with deep learning
- accelerate 3d backbone networks for autonomous driving
- pip install sparse convolution with cuda support

## When to choose
- you need high-performance spatial sparse convolution for point cloud networks
- you are building 3D detection or segmentation models on LiDAR data
- you want prebuilt wheels for specific CUDA versions on Linux

## When to avoid
- you need dense 2D convolutions or general-purpose deep learning frameworks
- you require Windows or macOS support
- your project needs only CPU inference on non-Linux platforms

## Facets
- artifact type: library
- maturity: active
- function: deep-learning, machine-learning, image-processing
- domain: deep-learning, computer-vision, autonomous-vehicles, machine-learning
- platform: python
- tags: sparse-convolution, point-cloud, 3d-perception, lidar, pytorch, tensorrt, linux, gpu, cuda

## Member repositories
- traveller59/spconv (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:34.964180+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:40:41.330090+00:00, confidence not recorded.
  - readme: https://github.com/traveller59/spconv (fetched 2026-08-28T04:06:34.964180+00:00, sha 93896198f15f)
  - registry_pypi: https://pypi.org/pypi/spconv/json (fetched 2026-08-29T10:20:52.113528+00:00, sha 5a01348e635c)
- Data as of 2026-08-30T08:39:29.467469+00:00.