# timzhang642/3D-Machine-Learning

A resource repository for 3D machine learning

Repository: https://github.com/timzhang642/3D-Machine-Learning
Canonical: https://ross.abutalabs.com/products/3d-machine-learning
License Family: other
Topics: 3d-reconstruction, papers, neural-networks, 3d, machine-learning, mesh, voxel, point-cloud, primitives, constructive-solid-geometries
Last push: 2024-07-04T19:13:09+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3308, "days_push": 790, "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 10193, forks 1798 (observed 2026-08-28T04:10:39.822110+00:00)

## What it is
A curated resource repository collecting courses, datasets, and research papers on 3D machine learning, an interdisciplinary field combining computer vision, computer graphics, and machine learning. It organizes papers by 3D representation type (multi-view images, volumetric, point cloud, mesh, primitives) and topic such as reconstruction, segmentation, and scene understanding.

## Use cases
- find research papers on 3D reconstruction with deep learning
- learn machine learning for 3D data
- find datasets of 3D models and scenes
- survey papers on point cloud and mesh processing
- find courses on geometric deep learning
- keep up with new 3D machine learning research

## When to choose
- you are starting research or study in 3D machine learning and need a curated reading list
- you need datasets or courses covering 3D vision and graphics topics
- you want to track papers by 3D representation type

## When to avoid
- you need runnable code or a software library rather than a paper list
- you need tutorials on general machine learning unrelated to 3D data

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, computer-vision, graphics, documentation
- domain: machine-learning, computer-vision, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, 3d-reconstruction, point-cloud, mesh, voxel, papers, research-papers, 3d-deep-learning

## Member repositories
- timzhang642/3D-Machine-Learning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:39.822110+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 2026-08-29T17:19:38.512511+00:00, confidence not recorded.
  - readme: https://github.com/timzhang642/3D-Machine-Learning (fetched 2026-08-28T04:10:39.822110+00:00, sha 22fbbb99a99e)
- Data as of 2026-08-30T08:39:29.467469+00:00.