# autonomousvision/mip-splatting

[CVPR'24 Best Student Paper] Mip-Splatting: Alias-free 3D Gaussian Splatting

Repository: https://github.com/autonomousvision/mip-splatting
Canonical: https://ross.abutalabs.com/products/mip-splatting
Homepage: https://niujinshuchong.github.io/mip-splatting/
Language: Python
License: NOASSERTION
License Family: other
Topics: 3d-reconstruction, guassian-splatting, nerf, novel-view-synthesis, anti-aliasing
Last push: 2024-12-17T10:42:50+00:00

## Health v2 (maintenance only)
Score: 27/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 72
- inputs: {"age_days": 1010, "days_push": 624, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1466, forks 121 (observed 2026-08-28T04:04:48.686499+00:00)

## What it is
Mip-Splatting is a research implementation of alias-free 3D Gaussian Splatting, introducing a 3D smoothing filter and 2D Mip filter to eliminate artifacts in novel view synthesis. It is the CVPR 2024 Best Student Paper codebase built on PyTorch with custom CUDA rasterization submodules.

## Use cases
- reconstruct 3D scenes from images with gaussian splatting
- render novel views without aliasing artifacts
- train on single-scale images and test at multiple scales
- evaluate on NeRF synthetic and Mip-NeRF 360 datasets
- compare 3DGS variants for research

## When to choose
- you need alias-free 3D Gaussian Splatting renderings across zoom levels
- you are doing research on novel view synthesis or NeRF alternatives
- you have a CUDA GPU and want state-of-the-art 3DGS quality

## When to avoid
- you need a production 3D viewer or end-user application
- you lack a CUDA-capable GPU
- you want a maintained product rather than research code

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, computer-vision, graphics, image-processing
- domain: computer-vision, graphics, deep-learning
- platform: python
- tags: 3d-gaussian-splatting, novel-view-synthesis, anti-aliasing, nerf, cvpr-2024, research-code, cuda-rasterization, linux, gpu

## Member repositories
- autonomousvision/mip-splatting (main) score 27

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:48.686499+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 2026-08-30T04:35:02.957096+00:00, confidence not recorded.
  - readme: https://github.com/autonomousvision/mip-splatting (fetched 2026-08-28T04:04:48.686499+00:00, sha d78a17dc62f6)
  - homepage: https://niujinshuchong.github.io/mip-splatting/ (fetched 2026-08-29T11:43:13.365071+00:00, sha b9f179fe13e2)
- Data as of 2026-08-30T08:39:29.467469+00:00.